CasGroup - User contributions [en]

Self-Star Properties

2008-09-19T16:43:51Z

213.218.25.117: /* Rejuvenation and Cancer */

'''Self-* properties''' refer to any properties or processes of a [[System|system]] which are caused and maintained by the system itself. They are an essential feature of living systems, and can be found in artificial systems as well: as an attempt to imitate and recreate the patterns and properties of natural [[Self-Organization|self-organizing systems]]. Self-* properties are useful for very [[Distributed System|distributed systems]], for example systems in [[Ubiquitous_Computing|ubiquitous computing]] or [[Pervasive Computing|pervasive computing]], or "megaservices", "megasystems" and giant-scale services with high [[Scalability|scalability]], i.e. Internet application on "planetary scale" with thousands of servers and millions of users.

== History ==

[[Image:Self.png|left|150px|]] A self-* process refers to any action which starts with "self-" and was caused by the system itself. A self-* property is a result of such a process. Already traditional mechanic machines and automata have self-properties. They are self-propelled and self-moving (in general "self-operating") machines which have automotive and automatic properties. They can run automatic and move themselves. Automatic refers to any self-operating machine or automaton (from the Greek automatos, "acting of one’s own will, self-moving").

Dijkstra introduced the notion of '''self-stabilization''' in the context of [[Distributed System|distributed systems]] in 1973. He defined a system as self-stabilizing when
"regardless of its initial state, it is guaranteed to arrive at a legitimate state in a
finite number of steps". The concept is therefore related to the mathematical
concept of an [http://en.wikipedia.org/wiki/Attractor attractor] in dynamical systems
and [http://en.wikipedia.org/wiki/Chaos_theory chaos theory].

A self-stabilizing system has two important properties:
*It does not need to be initialized
*It is [[Fault Tolerance|fault-tolerant]] and can recover from failures and faults

While it is obvious that self-stabilization is
a desirable property and possible in principle,
it is not clear how many self-stabilizing systems
and algorithms exist, and how fast a system converges
to a safe state. A recovery should occur in a
reasonable amount of time.
However, the construction of a self-stabilizing system
is still a difficult task, as Marco Schneider writes
in his survey (1993)

== Forms and Types ==

All positive processes like optimization, protection, recovery, etc. are of course desirable if they occur in autonomic systems without external guidance and control. In artificial software systems, the predominant approach is to use more a form of '''Self-Management''' instead of true [[Self-Organization|self-organization]] (i.e. organization completely without organizer). Self-management means the use of managers and managed elements to control and to manage a system. In their vision of [[Autonomic Computing|autonomic computing]], the IBM researcher Kephart and Chess mention the following four desirable self-* properties in autonomic systems: Self-configuration, Self-healing, Self-optimization and Self-protection.

[[Image:SelfStarProperties.png|thumb|400px|The basic Self-* Properties and the four sections of Autonomic Computing]]

'''Self-Configuration''' is the automated configuration of components and systems. Autonomic systems will configure themselves automatically in accordance with high-level policies that specify what is desired, not how it is to be accomplished. '''Self-Optimization''' means systems, sub-systems and components continually seek opportunities to improve their own performance and efficiency. It requires the autonomous ability of identifying and seizing opportunities to make the system more efficient in performance or cost. '''Self-Healing''' or '''Self-Repairing''' is the ability of a system to automatically detect, diagnose, and repair localized software and hardware problems.
Self-Healing requires monitoring, detection and diagnosis of faults and errors: an old Latin proverb
says "Bene diagnoscitur, bene curatur" (Something that is well diagnosed can be cured well).
'''Self-Stabilization''' refers to a system's ability to recover automatically from unexpected faults. '''Self-Protection''' is finally a property of systems which automatically defend themselves against malicious attacks or cascading failures. It uses early warning to anticipate and prevent systemwide failures. Other useful self-properties are related to analysis and diagnosis: '''Self-Describing''' and '''Self-Explaining''' systems are useful if we want to understand distributed systems which are getting more and more complex. They are also necessary for intelligent autonomous systems with the abilities of self-healing. Less intelligent systems must rely on restart of affected components, which is the foundation of the [[Recovery-Oriented Computing]] (ROC). All these properties are desirable, because the deploying, operating and maintaining of complex systems can be very costly, difficult and expensive. Modern [[Distributed System|distributed systems]] are inherently complex.

As the prefix self-* suggests, such self-* properties occur indeed often in self-organizing systems.
The usually involve some form of '''Self-Reference'''. Yet the existing self-* properties of living systems are not exactly identical with the desirable self-* properties of artificial systems. Living systems are characterized by the following self-* properties or self-organizing processes. What all living systems have in common is [[Autopoiesis]] and [[Self-Organization]]. '''Self-Regeneration''' and '''Self-Reproduction''' can be found even in plants through metabolism and sex (in Greek, 'metabolos' means something fluctuating or changing, that is always changing or in perpetual change)
, '''Self-Movement''', '''Self-Control''' and '''Self-Defense''' in animals due to digestion, cognition, and the immune system, and finally '''Self-Awareness''' and '''Self-Consciousness''' in humans. In other words the application of the principles found in natural systems to artificial and distributed systems is, unfortunately, not an easy, straightforward process. We cannot simply obtain amazing self-* properties in artificial systems just by imitating nature. A self-reproductive application is known as a dangerous virus, a self-defending system can be a nightmare, and a self-regenerative application can perhaps prevent a deactivation.

{| border="0" cellpadding="5" width="100%"
|-
! bgcolor="#ffffff" width="15%" align="left" |
! bgcolor="#77bb99" width="35%" align="left" | Self-* Properties in living system
! bgcolor="#aaaaaa" width="35%" align="left" | Self-* Properties in artificial system
! bgcolor="#ffffff" width="15%" align="left" |
|-

| bgcolor="#ffffff" valign="top" |

| bgcolor="#88ccaa" valign="top" |
in Plants
* Self-Regeneration
* Self-Reproduction

in Animals
* Self-Movement
* Self-Control
* Self-Defense

in Humans
* Self-Awareness
* Self-Consciousness
| bgcolor="#bbbbbb" valign="top" |
in Autonomic Systems
* Self-Optimization
* Self-Reconfiguration

in Fault-Tolerant Systems
* Self-Healing
* Self-Repairing
* Self-Protecting

in Self-Analyzing systems
* Self-Describing
* Self-Explaining
| bgcolor="#ffffff" valign="top" |

|}

Even desirable self-* properties can be a potential drawback: A self-describing or self-explaining application can be talkative or chatty, a self-optimizing and self-configuring system can reject manual changes, a self-protecting system can begin to attack itself (similar to allergies and autoimmune diseases), and a self-diagnostic application can be overcareful (Think of the Security Center in Windows XP: "Your computer might be at risk"). If these properties are implemented in autonomic and autonomous systems, they must be equipped with adjustable autonomy, i.e. the human administrator must always have the highest priority and the right to change every part of the system.

== Balancing Contradicting Properties ==

=== Self-Optimization and Self-Protection ===

[[Image:tradeoff1.png|thumb|365px|Trade-off between self-optimization and self-protection]]

One contradicting pair of self-* properties is self-optimization and self-protection.
Self-protection requires high security, strong protection and high encryption,
but high encryption in turn leads to low ease of use and high response or
reaction times for a system.
It would require too much time and effort to treat everything as top secret
with the highest possible encryption and protection. It would damage or endanger security
if nothing is really protected. Always highest encryption would take too much time
and effort, always lowest encryption would threaten security. A tradeoff between
both sides often results in classification or [http://en.wikipedia.org/wiki/Classified_information security levels],
for instance the well-known classification Top secret, Secret, Confidential, and Restricted.

=== Self-Optimization and Self-Reconfiguration ===

Another contradicting pair of self-* properties and capabilities is self-optimization
and self-reconfiguration. Self-optimization is possible by adaptation, and
strong adaptation to a certain problem can be an obstacle for easy reconfiguration
(see the "No Free Lunch Theorem" from Wolpert and Macready). In
the extreme case, a nerd or autistic savant has severe handicaps in solving
general problems but extraordinary abilities in a very special, limited area.

Another example are games, for example mobile robots for soccer games.
In order to optimize their behavior for a certain task, it useful to adapt them
to it as much as possible. If they play soccer it is useful to equip them with
special kickers, with special cameras and mirrors, and with special software
that recognizes only certain objects: goals (yellow or blue), fields (green),
balls (red) and dark obstacles which have the form of garbage cans. If they
are adapted in this way, the mobile robots can be used well to play soccer,
but they cannot be reconfigured easily for other games or completely other
tasks. Adaptation allows them to solve one special task well, but it makes
the reconfiguration for other tasks difficult.

A context-dependent trade-off for the conflict between optimization and
reconfiguration is possible by two things: first a dynamic adaptation (build
agents or robots which are able to learn from experience), and second a
dynamic type system for adaptive agents (build agents or robots which are
what they are doing, i.e. one has to optimize suitable agents for each situation
and context and tag them accordingly).

Dynamic context-dependent adaptation is realized in natural organisms
(esp. mammals) by the urge to play. It can be considered as a strategy
of organisms to organize and optimize their own behavior, even if future
situations are unpredictable. We play and laugh because it feels good: it
is rewarding and pleasant. At the same time, we learn the rules of the
game while we play. We gain new experience and new insights. We examine
different scenarios and try to find the best strategies. In this way, each
organism learns the behavior that is best in his context and situation. While
young animals play they explore the world, acquire knowledge and gain all
the necessary skills to survive. The desire to play drives animals to gain new
insights at the edge of their knowledge: well-known games are boring, too
complicated games are frustrating.

A dynamic type system for adaptive agents characterizes the adaptation
kind of each agent. Such a type system allows the selection of certain agents
for certain contexts. The type of an adaptive agent is changed by its roles
and activities. The longer an agent does something, the better it becomes.
Strong specialization and adaptation allow high performance and efficiency,
while the type system allows the exchange and selection of agents. For a
completely new tasks, new agents can trained.

=== Self-Optimization of contradicting properties ===

[[Image:tradeoff2.png|left|thumb|357px|Trade-off between reaction time and resource usage]]

One example for contradicting properties is the self-optimization of reaction
time and the self-optimization of resource usage. Optimal resource usage
is low, and optimal reaction time is also low, but both contradict each
other. Optimal reaction time requires high activity and high resource usage.
Full attention is necessary to react as fast as possible. On the contrary,
optimal resource usage leads to low activity and low reaction time. If only
occasional attention is required, resources can be spared. '''Stress''' is an important
trade-off between both sides: optimal response or reaction time on the
one hand and optimal resource usage on the other hand. It is the same form
of stress (or alarm of the body) that makes us sick if it occurs too frequently.

Stress means here the context-depent short-term activation of all available
resource, which are deactivated in the long term. It can occur in various
forms (readiness, alertness, preparedness, etc.), levels (severe, high, elevated,
low, etc.) and phases (for example alert phase in a fire brigade, or the three
emergency phases from the coast guard: uncertainty phase, alert phase, and
distress phase).

The DefCon leves from 1 to 6 of the american army and the different
threat levels of the Homeland Security Advisory System also belong into
this category. A level of high readiness or alertness is selected if the risk of
potential danger or the probability of an increased resource use in the near
future is very high. A level of low readiness and alertness is chosen if the
risk of potential danger or the probability of an increased resource use in the
future is very low.

=== Conclusion ===

Although conflicts between two contradicting self-* properties are not unusual,
the situation is not hopeless. A trade-off or compromise between two
contradicting self-* properties is possible. An optimal trade-off depends on
the relative importance of the properties compared to each other, on the situation
and the particular context of the system. It is often formulated as a set
of discrete levels. Security levels are such a trade-off between self-protection
and self-optimization. Always highest encryption would take too much time
and effort, always lowest encryption would endager security. Threat or stress
levels are similarly a trade-off between different kinds of self-optimization
(fast reaction and low resource usage). Although stress is associated with
negative things, it is the best compromise between too much resource usage
and too long response times. Alert and readiness levels are a universal compromise
which can be found everywhere in the real world where resources
have to be activated efficiently: in the military, in the fire brigade, in the
coast guard, etc.

== Drawbacks ==

=== Replication and Viruses ===

This is the most well-known example illustrating the drawback of a self-* property. A computer virus is a software system with the property of self-replication. It replicates and executes itself without the permission or knowledge of the user. Computer viruses can infect millions of computers. They will pass from one computer to another in the same way that a real life biological virus passes from person to person.

=== Healing, Preservation and Persistence ===

An essential element for the preservation and survival of cultures is education.
it Education is a self-* mechanism of a culture to preserve itself. It is also a
self-* mechanism to rejuvenate the elements of the system. This basic process
has to be distinguished from more complex self-* mechanisms to rejuvenate
the system itself, which are discussed later in the section about cancer and
rejuvenation.
There are many drawbacks of education as we all know: it can go wrong
if the wrong things are teached, it can have expansive and missionary effects,
and it can also preserve false beliefs and illusions.
A self-healing system that automatically repairs damage and also pinpoints
where it has been wounded would certainly be a good thing. But
what happens if the system uses this property or capability to keep working
although it is no longer necesarry? It could lead to robust applications or
systems which are not stopable or removable.
If there is a bug in the self-healing mechanism itself, it can also lead
to a worsening of the situation or to the destruction of the whole system.
Self-healing and self-protection are related to each other: protection against
intruders can prevent diseases which would requires healing.

=== Protection, Pain and Allergies ===

Pain is an unpleasant sensation resulting from the intricate interplay between
sensory and cognitive mechanisms. It is associated with actual or
potential tissue damage in natural organisms. Although it is unpleasant,
it is a necessary mechanism of systems with the capability of effective selfprotection.
Effective self-protection means fast self-protection. The rapid
warning through pain is a critical component of the body’s defense system.
Pain is an unpleasant sensation resulting from the intricate interplay between
sensory and cognitive mechanisms. A painful stimulus leads to a massive
activation of multiple units, and prevents at the same time any actions
associated with it. It is characterized by a loss in the flow of information, or
in the members of the system.

* A trainer of a sports team feels pain if his players are banned from the field, and he cannot send in new players.
* A general feel pain if his army loses in a continued campaign lots of soldiers, and he cannot replace them with new ones.
* A bishop feel pain if his church loses lots of members, while the number of new members is sinking, too. A chief of a political party will do the same

Pain seems to be a general, necessary mechanism of systems with the
capability of self-protection, because it signals the place where the selfprotecting
mechanisms fail.
Another negative side-effect of self-protection are autoimmune diseases
and allergies. In autoimmune diseases the body attacks the ‘self’ and its
own cells, examples are Diabetes Mellitus (type 1) or Multiple Sclerosis. In
allergies, the body attacks harmless targets which are normal parts of the
body: allergens such as dust, pollen, or certain foods. In both cases, the body
attacks parts of itself which are harmless. The distinction between self/nonself
and harmless/harmful goes wrong. In autoimmune diseases, parts of the
self are mistaken for hostile agents, and in allergies, harmless targets are
mistaken for harmful intruders.
Most autoimmune diseases are probably the result of multiple circumstances,
for example, a genetic predisposition triggered by an infection. Autoimmune
diseases result from at least three different interacting components:
genetic, environmental and regulatory. A unifying concept for the explanation
of an autoimmune disease needs “to incorporate genetic predisposition,
environmental factors and immune dysregulation”, as Ermann and Fathman
argue.

=== Rejuvenation and Cancer ===

Self-renewal is the key property of stem cells. Although they belong to the
most beneficial cells and enable rejuvenation and regeneration of the body,
they also seem to be at the heart of every tumor, as new reserch has found
out. Is it possible that the same cells which are responsible for
maintaining a tissue or an organ are also responsible for destroying it
through the worst form of disease?

A link between self-renewal, self-rejuvenation and self-reproduction would
perhaps explain why cancer is most common in the organs responsible for
self-reproduction: breast cancer or endometrial cancer in women, and prostate
cancer in men. It would also explain why “many of the body’s tissues that
are most prone to cancer, like the blood, skin and lining of the gut”
are self-regenerating tissues. These self-regenerating tissues are composed of
short-lived cells, and contain a self-renewing population of stem cells that
maintain them.

Cancer is a very complex disease. It can take years and decades until
enough mutations and damages are accumulated to enable a tumor. One
problem is that every tumor looks different.
Future research will hopefully shed more light on this complicated topic.
Recent research has found a close relationship between stem cells and tumor
generating cancer cells. Tumors seem to be the price for high
age. The reason is not only accumulated damage in form of progressive
deterioration, gradual abraison and inevitable wear and tear damages. Old
age is only possible through rejuvenation and repair. It looks like steems
cells which are responsible for renewal, rejuvenation and regeneration have
not only the ability to regenerate a system, but also the possibility to destroy
a system.

The more specialized an organism or a cell is, the more it seems to loose
its ability to replicate and regenerate itself. Stem cells are primal undifferentiated
cells that retain the ability to produce an identical copy of themselves,
whereas ordinary cells, specialized for a certain purpose, loose the ability to
produce an identical copy of themselves. Intermediary cells are restricted by
an internal counting mechanism to a finite number of cell divisions, which
declines with increasing differentiation.

Has this something to do with the unique history of each organism or
cell (are old, highly differentiated and specialized cells usually polluted or
used up) ? Or is this hierarchy useful for avoiding chaos and confusing which
could arise if every cell would be allowed to replicate itself?
If no cells would be able to copy and replicate itself, then the body would
not be able to rejuvenate and repair itself in order to replace damaged or old
cells. If all cells would be able to do this, this would result in ”chaos” and
every cell would be a potential cancer cell. It looks like Nature has invented
a compromise in form of stem cells.
Stem cells are a blessing, because they can replace damaged or old cells,
but mutated or damaged stem cells are a curse. Stem cells have like tumor
generating cancer cells the same potential to proliferate, they have an
unlimited life span and the ability to generate a diverse range of other cell
types.

New research gives strong evidence that cancer is the price for an
evovable system (subject to mutation) with the ability of self-replication, selfrejuvenation
and self-repair. It seems to be the price for the self-* properties
which enable our existence and keep us alive. Perhaps this helps to explain
why it is so difficult to find a cure for it. Recently, researchers have suggest
again new strategies to fight cancer, for instance viruses (modified common
cold viruses), chillies (spicy food) or sugars (a combination of sugar and
short-chain fatty acid). So far, there is no miracle cure for cancer. And
probably none of these new approaches will be a miracle cure, either. But
hopefully one approach in the future - perhaps due to the new insight that
the disease is related to self-rejuvenation - will lead to something useful in
the ongoing battle against this terrible disease.

This rises the urgent question if artificial systems can develop some form
of cancer, too, if we try to build systems with these very desirable self-*
properties. Is there a form of cancer in complex adaptive systems in general,
not only in biological organisms, but also in ecological, economical, social or
political systems ? This would perhaps be an element arising from the need
for self-rejuvenation which proliferates, spreads and replicates itself until it
has destroyed the whole system.

* Ecologies systems allow the self-rejuvenation by “granting the right” to create new species and to explore new ways to survive. In an ecological system, this freedom can lead to mass extinctions or epedimics caused by parasites or viruses with the capacity to damage or destroy the whole ecological system.

* Economies allow the self-rejuvenation by granting the right to found new companies and to explore new market forms. In an economical system, this freedom can lead to market monopolies, which destroy the market system. Democracies allow the self-rejuvenation by granting the rights to found new parties, to assemble, to demonstrate, and to educate. In a political system, this can lead to terrorism or an ideology like fascism. In a religious system, it can lead to schisms and sects.

* Science allows the self-rejuvenation by “granting the right” to create new theories and to explore new ways to explain nature. This freedom can lead to subsystems with the capacity to threaten the whole scientific system, for example in form of a paradigm shift.

In general, if a [[Complex_Adaptive_System|complex adpative system]] has a built-in self-rejuvenation ability, and it grants it’s agents the rights to create and to found new elements, these elements can severely damage or threaten the function of the whole system. Any system which is able to remould and reinvent itself can replace itself by something else.

=== Conclusion ===

In general, any self-* mechanism or self-* property is acting on “the self”,
and it can destroy, damage or threaten the system - the self - if something
goes wrong. The postive consequences are wonderful, but the negative consequences
and side-effects of self-* properties range from unpleasant to disastrous:

* self-healing, self-rejuvenation -> cancer
* self-protection -> pain, allergies, and autoimmune diseases
* self-reconfiguration -> errors, faults, and failures
* self-optimizing -> slow-down, halt, stop

Any strong self-* property could also lead to rejection or overwriting of
manual changes, or to the inability to deactive the system - to the loss of
control. The fear that we will lose control of our software, if it is modified to
be more like living systems is justified.

Do we really want to build autonomous or autonomic systems with self-*
properties? Self-protecting systems that can feel pain and are able to attack
themselves? Bugs appear everywhere. Things can always go wrong, and if
things go wrong in the code for the self-* properties itself, the result can be
disastrous and utterly devastating. It is possible that we open the box of
pandora if we build systems with deeply embedded self-* properties.

== Papers ==

Jeffrey O. Kephart and David M. Chess, ''The Vision of Autonomic Computing'', IEEE Computer, January 2003
[http://www.research.ibm.com/autonomic/research/papers/AC_Vision_Computer_Jan_2003.pdf]

Marco Schneider, [http://portal.acm.org/citation.cfm?id=151256 Self-stabilization], ACM Computing Surveys, 25, 45–67 (1993)

== Links ==

* [http://www.cs.unibo.it/self-star/ Self-STAR: International Workshop on Self-* Properties in Complex Information Systems]

* Michael F. Clarke Irving L. Weissman Tannishtha Reya, Sean J. Morrison, [http://www.iscbm.ucla.edu/documents/Week4Reya.pdf Stem cells, cancer, and cancer stem cells] Nature 414 (2004), no. 6859, 105–111. 4.4.5

* Nicholas Wade, [http://www.nytimes.com/2006/02/21/health/21canc.html Stem Cells May Be Key to Cancer] New York Times February 21 (2006).

* Gina Kolata, [http://www.nytimes.com/2005/12/27/health/27canc.html Slowly, cancer genes tender their secrets, New York Times], December 27 (2005).

== Books ==

Shlomi Dolev, ''Self-Stabilization'', The MIT Press, 2000, ISBN 0-262-04178-2

[[Category:Applied Principles]]
[[Category:Consciousness]]

Emergence

2008-09-19T09:08:05Z

213.218.25.117: /* Difficult Examples */

[[Image:Classic_View_of_Emergence.png|thumb|300px|The classic view of "emergence"]]

'''Emergence''' is a process which describes the appearance of emergent properties and phenomena. A property of a system is emergent, if it is not a property of any fundamental element. Composite entities can have properties that can not be found in the parts of the composition. In other words, emergence happens if "more is different", if there are properties of a group which can not be explained by the properties of the parts, entities and [[Agent|agents]] alone.

== Introduction ==

An emergent behavior is not imposed from the outside by a central controller or organizer,
it results solely from the interactions between the agents.
Emergence is a characteristic feature of many [[Complex System|complex]] and [[Self-Organization|self-organizing]] systems. Emergence and self-organization seem to be a contradiction to the second law of thermodynamics, which says that organization and order can not increase in isolated systems. They are possible because they usually happen in open systems, which extract information and order out of the environment and produce waste (import of order/information and export of disorder/entropy). The process of self-organization refers to the boundary between system and environment, the process of emergence involves the microscopic-macroscopic boundary between the individual and the collective group.

== Types and Forms ==

One can distinguish roughly between four types of emergence: (1) Simple/Nominal Emergence (2) Weak Emergence (3) Multiple Emergence (4) Strong Emergence. They can be distinguished by the different degree of predictability and the different types of roles.

=== Overview ===

{| border="0" cellpadding="5" width="100%"
|-
! bgcolor="#70b0e0" width="25%" align="left" | Type and Name
! bgcolor="#eedd90" width="25%" align="left" | Roles
! bgcolor="#bbbbbb" width="25%" align="left" | Frequency
! bgcolor="#77bb99" align="left" | Predictability
|-
| bgcolor="#80c0ff" valign="top" |
I Nominal or Intentional 
II Weak 
III Multiple 
IV Strong 

| bgcolor="#ffeea0" valign="top" |
Fixed 
Flexible 
Fluctating 
New World of Roles 

| bgcolor="#cccccc" valign="top" |
Abundant 
Frequent 
Common - Unusual 
Rare 

| bgcolor="#88ccaa" valign="top" |
totally predictable 
predictable in principle 
not predictable (chaotic) 
not predictable, even in principle 

|}

=== 1. Simple/Nominal Emergence (Type I) ===

The weakest possible sense is totally predictable, and has the strongest form of constraints: each component and element has a fixed and constant role, which is not allowed to change in the course of time. A system in form of a machine has for instance a function which is different from the function of the parts and components, but the overall function is well-known, and it only matches the planned and designed function. There are no unpredicted or unexpected behavior patterns.

{{SelfOrg}}

=== 2. Weak Emergence (Type II) ===

[[Image:Emergence.gif|left|Weak Emergence]] Weak emergence is the most common form of emergence related to swarms, flocks and other social groups. It describes emergence forms with simple feedback, which is predictable in principle, but not in every detail. The roles of the elements and agents are flexible (for example "transporter", "explorer", "defender" and "follower" in ant colonies. It is the classic form of emergence, which can be seen in the figure on the left side: coherent global structures appear and become visible on a higher level of organization through the local interaction of several autonomous agents. Top-down feedback from the group imposes in turn constraints on the local interactions. An example is a flock of Geese, which limits the possible movements of the individual birds. An important element is context-dependence: agents ajust their behavior and their role in the group according to the actual context and situation. Feedback from the group or the environment to the agent is possible through this form of context-dependent flexibility.

=== 3. Multiple Emergence (Type III) ===

Multiple emergence is a form of emergence with multiple positive and negative feedback loops. The behavior is not predictable, and can be chaotic. Completely new roles can appear, while old roles disappear.
A typical example for multiple emergence are bubbles are droplets.
M. Mitchell Waldrop says in his book "Complexity:
The Emerging Science at the Edge of Order and Chaos "
(Simon & Schuster, 1992) about the complex patterns of droplets :

"Imagine spilling a little water onto the surface of a
highly polished tray, (..) it beads up into a complex
pattern of droplets. And it does so because two countervailing
forces are at work. There is gravity, which tries to spread
out the water to make a very thin, flat film across the
whole surface. That's negative feedback. And there is surface
tension, the attraction of one water molecule to another,
which tries to pull the liquid together into compact globules.
That's positive feedback. It's the mix of the two forces
that produces the complex patterns of beads. Moreover, that
pattern is unique. Try the experiment again and you'll get
a completely different arrangement of droplets. Tiny
accidents of history - infinitesimal dust motes and
invisible irregularities in the surface of the tray -
get magnified by the positive feedback into major
differences in the outcome." (page 36)

=== 4. Strong Emergence (Type IV) ===

[[Image:Code.gif|left|Strong Emergence]] The strongest possible sense of emergence is related to supervenience, the weakest form of causal dependence. It is not predictable, even in principle, because it describes the appearance of a new [[Code|code]] or completely new [[System|system]] in a multi-level or multi-scale system with many levels. Combinatorial explosion renders any attempt of explaining emergent macroscopic, high-level phenomena in terms of microscopic low-level phenomena useless and futile. An intermediate or mesoscopic level often protects the macroscopic level from the microscopic level, i.e. the microscopic level is irrelevant to the behavior of the macroscopic level. Therefore strong emergence can be considered as crossing the barrier of relevance.

Strong emergence is very rare, and is normally the result of a long [[evolution|evolutionary process]], or the result of deliberate and intentional design. Classic examples for strong emergence are the appearance of life and living systems through the emergence of the genetic code, and the appearance of culture and cultural systems through the emergence of memetic code (i.e. linguistic codes and languages in general). In both cases, completely new evolutionary or [[Complex Adaptive System|complex adaptive systems]] appeared, which are subject to their own [[Evolution|evolution]].

Strong emergence can be distinguished from weak by the existence of a code which specifies a new
system in a system. Strong emergence is the emergence of a whole new system, with new building blocks and
interaction laws. The "strong" emergence of a system is identical or at least closely related to the simulation
or representation of a system through another system - simulation is the attempt to represent certain features
of the behavior of a system by the behavior of another system. The interface between the new and the old
system is described by a new code or language.

Characteristic signs for strong emergence are the existence of
*adaptors between two independent worlds
*codes and languages which define a correspondence between two independent worlds
*a multi-level or multi-scale system with many levels
*mesoscopic levels between the microscopic level of the individual cells, elements and agents, and the macroscopic level of the total system

=== Shadow Emergence (special case) ===

see [[Shadow_Emergence|Shadow Emergence]]

== Emergence and Evolution ==

[[Image:EmergenceEvolution.png|thumb|right|295px|The influence of self-organization and evolution in different emergence types]]

While [[Self-Organization|self-organization]] is frequently seen as the
cause for complexity in nature (since nobody "organizes" nature),
emergence is sometimes mistaken for the origin of jumps in complexity.
Yet neither self-organization nor emergence is responsible for overwhelming
complexity heights or sudden changes in complexity.
Simple forms of emergence (Type I, Type II and partially Type III) can
be considered as the result of [[Self-Organization|self-organization]].
This form is often temporary or instable: flocks dissolve,
schools of fish dissociate, and social groups disintegrate
after a while.

The real jumps in complexity are related to emergence in
[[Evolutionary System|evolutionary systems]].
[[Evolution|Evolution]] is still the main reason and the driving
force for the complexity and diversity which can be found in nature,
and neither the concept of self-organization nor the phenomenon
of emergence can really replace evolution or natural
selection. The evolution of "selfish genes" seems to be responsible
itself for all forms of sudden jumps in complexity in
history, i.e. the appearance of more and more complex
species or complex properties in the course of time.

Evolution is also responsible for all forms of "strong emergence" (Type IV),
in which whole new evolutionary systems appear
(associated with the emergence of a new code
which is used to create the new evolutionary system).
A new [[Code|code]] marks the limits between the
type I-III emergence due to forced extrinsic organization
and intrinsic [[Self-Organization|self-organization]],
and the type IV emergence due to evolution and deliberate
design of a new code. It also marks the limits of
[[Self-Organization|self-organization]] in general.

Sudden jumps in complexity due to evolution are often
related to fitness barriers. There are at least three different
ways to cope with fitness barriers in evolution (Type IIIb),
(1) bypass it, (2) tunnel through it, or (3) overcome it:

# to bypass through [[Exaptation|exaptation]]: explore a different direction and make a sudden side-leap
# to tunnel right through the barrier by borrowing [[Complexity|complexity]]
# to wait for a catastrophe, until the barrier is reduced through catastrophic events

== Examples ==

=== Classic Examples ===

[[Image:Langton.png|thumb|right|295px|Langton's Ant]]
Christopher '''Langton's Ant''' and John Von Neumann's
self-reproducing automata belong to the classic
examples of "emergence", besides '''Conway's Game of Life'''
from the field of ALife and '''Schelling's segregation model'''
from the social sciences.

Langton's Ant is sometimes considered as a [[Cellular_Automata|cellular automata]],
but it is more like an agent-based simulation with just
one agent: the ant that wanders around.
The rules for "Langton's Ant" are remarkably simple:
*If the ant is on a white cell it turns left 90 degrees and moves one unit forward
*If the ant is on a black cell it turns right 90 degrees and moves one unit forward
*As the ant moves to the next cell, the one that it is on changes color from white to black, or the reverse.

They can be formulated even simpler:
*The ant reverses the color of any cell it visits.
*When the ant visits a white square it turns left; when it visits a black square it turns right.

When the ant is started on an empty grid, these simple rules result
first in very comlex and chaotic pattern,
but after about ten thousand moves the ant suddenly
shows a repetitive pattern: it gets locked into a periood
or cycle of 104 steps and tries to build a broad diagonal
"highway", each time displacing the ant two pixels vertically
and horizontally. It is a good example for [[Stigmergy|stigmergy]]
and Type II emergence: the ant changes the environment
(the micro-macro direction), and the environment changes
in turn the behavior of the ant (the macro-micro feedback).

There are many applets for Langton's Ant on the net, for example [http://users.libero.it/acnard/ant.html] and
[http://www.math.ubc.ca/~cass/www/ant/ant.html].
[http://mathworld.wolfram.com/LangtonsAnt.html Mathworld] says it is a "4-state 2-dimensional Turing machine".

If a single agent which follows very simple rules
can produce such a complex behavior pattern,
then the behavior of a whole [[Multi-Agent System]]
with multiple agents and many different [[Agent|agent]]
types is of course much more complicated.

The self-reproducing automata from John Von Neumann
(and later from Edgar Codd) is more like a [[Cellular_Automata|cellular automata]]
and was deliberately constructed as a kind of
"self-reproducing machine", see [http://stud4.tuwien.ac.at/~e0125222/codd/].

=== Simple Examples ===

The simplest form of emergence is probably the following.
To build a single termite mound in an environment
consisting of randomly-scattered wood chips, a group
of termites each has only to follow one simple rule :

While wandering randomly
*if you find a chip then pick it up
*unless you're already carrying a chip in which case drop it

These simple rules lead to an automatic aggregation of chips and "heap formation". Several small heaps will start to emerge, but then the largest heap will grow at the expense of the smaller ones until there is only the larger one left, see [http://www.beart.org.uk/Emergent/index.htm] and
[http://ccl.northwestern.edu/netlogo/models/Termites].

=== Other Examples ===

The following phenomena are examples for emergent properties:

*a "who eats whom" foodweb is an emergent property of a complex ecosystem. It emerges as a stable, repeated pattern in a complex ecosystem

*a supply chain network is an emergent property of a complex economic system

*PageRank is an algorithm developed by Google to determine a web pages "inbound link ranking". The rank of each page is an emergent property. A Web page alone is hard to evaluate regarding its usefulness, correctness, and popularity, but taken together, all Web pages do give useful information, which can be extracted with the PageRank algorithm.

* a painting emerges from the unique combination of colored points, strokes and lines created by the painter, similar to a book which arises from a unique combination of letters, or a piece of music (all Type I)

=== Difficult Examples ===

Everything arises from atoms. Genes shape
life-forms. Brain chemicals shape behavior.
Assemblies of neurons shape [[Self-Consciousness|self-consciousness]]
and thoughts. Just how exactly?

== Articles and Papers ==

Jochen Fromm's following preprints
* [http://arxiv.org/abs/nlin.AO/0506028 Types and Forms of Emergence]
* [http://arxiv.org/abs/nlin.AO/0509049 Ten Questions about Emergence]
* [http://arxiv.org/abs/nlin.AO/0601002 On Engineering and Emergence]

Shalizi's notebook entry on [http://cscs.umich.edu/~crshalizi/notebooks/emergent-properties.html Emergent Properties]

== Books ==
* John H. Holland, ''Emergence from chaos to order'' (1998) Oxford University Press, ISBN 0738201421
* Steven Johnson, ''Emergence'' (2002) Scribner, ISBN 0684868768
* Stephen Wolfram, ''[http://www.wolframscience.com/nksonline/toc.html A New Kind of Science]'' (2002), ISBN 1579550088.
* Jochen Fromm, ''[http://www.upress.uni-kassel.de/abstracts/3-89958-069-9.html The emergence of complexity]'' (2004) Kassel University Press, ISBN 3899580699
* Thomas C. Schelling, ''Micromotives and Macrobehavior'' (1978) W. W. Norton and Company
* Harold J. Morowitz, ''The Emergence of Everything: How the World Became Complex'' (2002) Oxford University Press, ISBN 019513513X
* Armand Delsemme, ''Our Cosmic Origins: From the Big Bang to the Emergence of Life and Intelligence'' (1998) Cambridge University Press
* John Maynard Smith and Eörs Szathmáry, ''The Major Transitions in Evolution'' (1997) Oxford University Press, ISBN 019850294X

==External links==

* [http://llk.media.mit.edu/projects/emergence/ Exploring Emergence]: An introduction to emergence using [[Conway's Game of Life]] from the [[MIT Media Lab]]
* [http://plato.stanford.edu/entries/properties-emergent/ Stanford Encyclopedia of Philosophy entry on Emergent Properties]
* Russ Abbott's [http://cs.calstatela.edu/~wiki/index.php/Courses/CS_461/Museum_of_unintended_consequences Museum of unintended consequences] in social systems and everyday life

[[Category:Basic Principles]]

Emergence

2008-09-19T09:06:00Z

213.218.25.117: /* Other Examples */

[[Image:Classic_View_of_Emergence.png|thumb|300px|The classic view of "emergence"]]

'''Emergence''' is a process which describes the appearance of emergent properties and phenomena. A property of a system is emergent, if it is not a property of any fundamental element. Composite entities can have properties that can not be found in the parts of the composition. In other words, emergence happens if "more is different", if there are properties of a group which can not be explained by the properties of the parts, entities and [[Agent|agents]] alone.

== Introduction ==

An emergent behavior is not imposed from the outside by a central controller or organizer,
it results solely from the interactions between the agents.
Emergence is a characteristic feature of many [[Complex System|complex]] and [[Self-Organization|self-organizing]] systems. Emergence and self-organization seem to be a contradiction to the second law of thermodynamics, which says that organization and order can not increase in isolated systems. They are possible because they usually happen in open systems, which extract information and order out of the environment and produce waste (import of order/information and export of disorder/entropy). The process of self-organization refers to the boundary between system and environment, the process of emergence involves the microscopic-macroscopic boundary between the individual and the collective group.

== Types and Forms ==

One can distinguish roughly between four types of emergence: (1) Simple/Nominal Emergence (2) Weak Emergence (3) Multiple Emergence (4) Strong Emergence. They can be distinguished by the different degree of predictability and the different types of roles.

=== Overview ===

{| border="0" cellpadding="5" width="100%"
|-
! bgcolor="#70b0e0" width="25%" align="left" | Type and Name
! bgcolor="#eedd90" width="25%" align="left" | Roles
! bgcolor="#bbbbbb" width="25%" align="left" | Frequency
! bgcolor="#77bb99" align="left" | Predictability
|-
| bgcolor="#80c0ff" valign="top" |
I Nominal or Intentional 
II Weak 
III Multiple 
IV Strong 

| bgcolor="#ffeea0" valign="top" |
Fixed 
Flexible 
Fluctating 
New World of Roles 

| bgcolor="#cccccc" valign="top" |
Abundant 
Frequent 
Common - Unusual 
Rare 

| bgcolor="#88ccaa" valign="top" |
totally predictable 
predictable in principle 
not predictable (chaotic) 
not predictable, even in principle 

|}

=== 1. Simple/Nominal Emergence (Type I) ===

The weakest possible sense is totally predictable, and has the strongest form of constraints: each component and element has a fixed and constant role, which is not allowed to change in the course of time. A system in form of a machine has for instance a function which is different from the function of the parts and components, but the overall function is well-known, and it only matches the planned and designed function. There are no unpredicted or unexpected behavior patterns.

{{SelfOrg}}

=== 2. Weak Emergence (Type II) ===

[[Image:Emergence.gif|left|Weak Emergence]] Weak emergence is the most common form of emergence related to swarms, flocks and other social groups. It describes emergence forms with simple feedback, which is predictable in principle, but not in every detail. The roles of the elements and agents are flexible (for example "transporter", "explorer", "defender" and "follower" in ant colonies. It is the classic form of emergence, which can be seen in the figure on the left side: coherent global structures appear and become visible on a higher level of organization through the local interaction of several autonomous agents. Top-down feedback from the group imposes in turn constraints on the local interactions. An example is a flock of Geese, which limits the possible movements of the individual birds. An important element is context-dependence: agents ajust their behavior and their role in the group according to the actual context and situation. Feedback from the group or the environment to the agent is possible through this form of context-dependent flexibility.

=== 3. Multiple Emergence (Type III) ===

Multiple emergence is a form of emergence with multiple positive and negative feedback loops. The behavior is not predictable, and can be chaotic. Completely new roles can appear, while old roles disappear.
A typical example for multiple emergence are bubbles are droplets.
M. Mitchell Waldrop says in his book "Complexity:
The Emerging Science at the Edge of Order and Chaos "
(Simon & Schuster, 1992) about the complex patterns of droplets :

"Imagine spilling a little water onto the surface of a
highly polished tray, (..) it beads up into a complex
pattern of droplets. And it does so because two countervailing
forces are at work. There is gravity, which tries to spread
out the water to make a very thin, flat film across the
whole surface. That's negative feedback. And there is surface
tension, the attraction of one water molecule to another,
which tries to pull the liquid together into compact globules.
That's positive feedback. It's the mix of the two forces
that produces the complex patterns of beads. Moreover, that
pattern is unique. Try the experiment again and you'll get
a completely different arrangement of droplets. Tiny
accidents of history - infinitesimal dust motes and
invisible irregularities in the surface of the tray -
get magnified by the positive feedback into major
differences in the outcome." (page 36)

=== 4. Strong Emergence (Type IV) ===

[[Image:Code.gif|left|Strong Emergence]] The strongest possible sense of emergence is related to supervenience, the weakest form of causal dependence. It is not predictable, even in principle, because it describes the appearance of a new [[Code|code]] or completely new [[System|system]] in a multi-level or multi-scale system with many levels. Combinatorial explosion renders any attempt of explaining emergent macroscopic, high-level phenomena in terms of microscopic low-level phenomena useless and futile. An intermediate or mesoscopic level often protects the macroscopic level from the microscopic level, i.e. the microscopic level is irrelevant to the behavior of the macroscopic level. Therefore strong emergence can be considered as crossing the barrier of relevance.

Strong emergence is very rare, and is normally the result of a long [[evolution|evolutionary process]], or the result of deliberate and intentional design. Classic examples for strong emergence are the appearance of life and living systems through the emergence of the genetic code, and the appearance of culture and cultural systems through the emergence of memetic code (i.e. linguistic codes and languages in general). In both cases, completely new evolutionary or [[Complex Adaptive System|complex adaptive systems]] appeared, which are subject to their own [[Evolution|evolution]].

Strong emergence can be distinguished from weak by the existence of a code which specifies a new
system in a system. Strong emergence is the emergence of a whole new system, with new building blocks and
interaction laws. The "strong" emergence of a system is identical or at least closely related to the simulation
or representation of a system through another system - simulation is the attempt to represent certain features
of the behavior of a system by the behavior of another system. The interface between the new and the old
system is described by a new code or language.

Characteristic signs for strong emergence are the existence of
*adaptors between two independent worlds
*codes and languages which define a correspondence between two independent worlds
*a multi-level or multi-scale system with many levels
*mesoscopic levels between the microscopic level of the individual cells, elements and agents, and the macroscopic level of the total system

=== Shadow Emergence (special case) ===

see [[Shadow_Emergence|Shadow Emergence]]

== Emergence and Evolution ==

[[Image:EmergenceEvolution.png|thumb|right|295px|The influence of self-organization and evolution in different emergence types]]

While [[Self-Organization|self-organization]] is frequently seen as the
cause for complexity in nature (since nobody "organizes" nature),
emergence is sometimes mistaken for the origin of jumps in complexity.
Yet neither self-organization nor emergence is responsible for overwhelming
complexity heights or sudden changes in complexity.
Simple forms of emergence (Type I, Type II and partially Type III) can
be considered as the result of [[Self-Organization|self-organization]].
This form is often temporary or instable: flocks dissolve,
schools of fish dissociate, and social groups disintegrate
after a while.

The real jumps in complexity are related to emergence in
[[Evolutionary System|evolutionary systems]].
[[Evolution|Evolution]] is still the main reason and the driving
force for the complexity and diversity which can be found in nature,
and neither the concept of self-organization nor the phenomenon
of emergence can really replace evolution or natural
selection. The evolution of "selfish genes" seems to be responsible
itself for all forms of sudden jumps in complexity in
history, i.e. the appearance of more and more complex
species or complex properties in the course of time.

Evolution is also responsible for all forms of "strong emergence" (Type IV),
in which whole new evolutionary systems appear
(associated with the emergence of a new code
which is used to create the new evolutionary system).
A new [[Code|code]] marks the limits between the
type I-III emergence due to forced extrinsic organization
and intrinsic [[Self-Organization|self-organization]],
and the type IV emergence due to evolution and deliberate
design of a new code. It also marks the limits of
[[Self-Organization|self-organization]] in general.

Sudden jumps in complexity due to evolution are often
related to fitness barriers. There are at least three different
ways to cope with fitness barriers in evolution (Type IIIb),
(1) bypass it, (2) tunnel through it, or (3) overcome it:

# to bypass through [[Exaptation|exaptation]]: explore a different direction and make a sudden side-leap
# to tunnel right through the barrier by borrowing [[Complexity|complexity]]
# to wait for a catastrophe, until the barrier is reduced through catastrophic events

== Examples ==

=== Classic Examples ===

[[Image:Langton.png|thumb|right|295px|Langton's Ant]]
Christopher '''Langton's Ant''' and John Von Neumann's
self-reproducing automata belong to the classic
examples of "emergence", besides '''Conway's Game of Life'''
from the field of ALife and '''Schelling's segregation model'''
from the social sciences.

Langton's Ant is sometimes considered as a [[Cellular_Automata|cellular automata]],
but it is more like an agent-based simulation with just
one agent: the ant that wanders around.
The rules for "Langton's Ant" are remarkably simple:
*If the ant is on a white cell it turns left 90 degrees and moves one unit forward
*If the ant is on a black cell it turns right 90 degrees and moves one unit forward
*As the ant moves to the next cell, the one that it is on changes color from white to black, or the reverse.

They can be formulated even simpler:
*The ant reverses the color of any cell it visits.
*When the ant visits a white square it turns left; when it visits a black square it turns right.

When the ant is started on an empty grid, these simple rules result
first in very comlex and chaotic pattern,
but after about ten thousand moves the ant suddenly
shows a repetitive pattern: it gets locked into a periood
or cycle of 104 steps and tries to build a broad diagonal
"highway", each time displacing the ant two pixels vertically
and horizontally. It is a good example for [[Stigmergy|stigmergy]]
and Type II emergence: the ant changes the environment
(the micro-macro direction), and the environment changes
in turn the behavior of the ant (the macro-micro feedback).

There are many applets for Langton's Ant on the net, for example [http://users.libero.it/acnard/ant.html] and
[http://www.math.ubc.ca/~cass/www/ant/ant.html].
[http://mathworld.wolfram.com/LangtonsAnt.html Mathworld] says it is a "4-state 2-dimensional Turing machine".

If a single agent which follows very simple rules
can produce such a complex behavior pattern,
then the behavior of a whole [[Multi-Agent System]]
with multiple agents and many different [[Agent|agent]]
types is of course much more complicated.

The self-reproducing automata from John Von Neumann
(and later from Edgar Codd) is more like a [[Cellular_Automata|cellular automata]]
and was deliberately constructed as a kind of
"self-reproducing machine", see [http://stud4.tuwien.ac.at/~e0125222/codd/].

=== Simple Examples ===

The simplest form of emergence is probably the following.
To build a single termite mound in an environment
consisting of randomly-scattered wood chips, a group
of termites each has only to follow one simple rule :

While wandering randomly
*if you find a chip then pick it up
*unless you're already carrying a chip in which case drop it

These simple rules lead to an automatic aggregation of chips and "heap formation". Several small heaps will start to emerge, but then the largest heap will grow at the expense of the smaller ones until there is only the larger one left, see [http://www.beart.org.uk/Emergent/index.htm] and
[http://ccl.northwestern.edu/netlogo/models/Termites].

=== Other Examples ===

The following phenomena are examples for emergent properties:

*a "who eats whom" foodweb is an emergent property of a complex ecosystem. It emerges as a stable, repeated pattern in a complex ecosystem

*a supply chain network is an emergent property of a complex economic system

*PageRank is an algorithm developed by Google to determine a web pages "inbound link ranking". The rank of each page is an emergent property. A Web page alone is hard to evaluate regarding its usefulness, correctness, and popularity, but taken together, all Web pages do give useful information, which can be extracted with the PageRank algorithm.

* a painting emerges from the unique combination of colored points, strokes and lines created by the painter, similar to a book which arises from a unique combination of letters, or a piece of music (all Type I)

=== Difficult Examples ===

Everything arises from atoms. Genes shape
life-forms. Brain chemicals shape behavior.
Assemblies of neurons shape consciousness
and thoughts. Just how exactly?

== Articles and Papers ==

Jochen Fromm's following preprints
* [http://arxiv.org/abs/nlin.AO/0506028 Types and Forms of Emergence]
* [http://arxiv.org/abs/nlin.AO/0509049 Ten Questions about Emergence]
* [http://arxiv.org/abs/nlin.AO/0601002 On Engineering and Emergence]

Shalizi's notebook entry on [http://cscs.umich.edu/~crshalizi/notebooks/emergent-properties.html Emergent Properties]

== Books ==
* John H. Holland, ''Emergence from chaos to order'' (1998) Oxford University Press, ISBN 0738201421
* Steven Johnson, ''Emergence'' (2002) Scribner, ISBN 0684868768
* Stephen Wolfram, ''[http://www.wolframscience.com/nksonline/toc.html A New Kind of Science]'' (2002), ISBN 1579550088.
* Jochen Fromm, ''[http://www.upress.uni-kassel.de/abstracts/3-89958-069-9.html The emergence of complexity]'' (2004) Kassel University Press, ISBN 3899580699
* Thomas C. Schelling, ''Micromotives and Macrobehavior'' (1978) W. W. Norton and Company
* Harold J. Morowitz, ''The Emergence of Everything: How the World Became Complex'' (2002) Oxford University Press, ISBN 019513513X
* Armand Delsemme, ''Our Cosmic Origins: From the Big Bang to the Emergence of Life and Intelligence'' (1998) Cambridge University Press
* John Maynard Smith and Eörs Szathmáry, ''The Major Transitions in Evolution'' (1997) Oxford University Press, ISBN 019850294X

==External links==

* [http://llk.media.mit.edu/projects/emergence/ Exploring Emergence]: An introduction to emergence using [[Conway's Game of Life]] from the [[MIT Media Lab]]
* [http://plato.stanford.edu/entries/properties-emergent/ Stanford Encyclopedia of Philosophy entry on Emergent Properties]
* Russ Abbott's [http://cs.calstatela.edu/~wiki/index.php/Courses/CS_461/Museum_of_unintended_consequences Museum of unintended consequences] in social systems and everyday life

[[Category:Basic Principles]]

Emergence

2008-09-19T09:05:36Z

213.218.25.117: /* Other Examples */

[[Image:Classic_View_of_Emergence.png|thumb|300px|The classic view of "emergence"]]

'''Emergence''' is a process which describes the appearance of emergent properties and phenomena. A property of a system is emergent, if it is not a property of any fundamental element. Composite entities can have properties that can not be found in the parts of the composition. In other words, emergence happens if "more is different", if there are properties of a group which can not be explained by the properties of the parts, entities and [[Agent|agents]] alone.

== Introduction ==

An emergent behavior is not imposed from the outside by a central controller or organizer,
it results solely from the interactions between the agents.
Emergence is a characteristic feature of many [[Complex System|complex]] and [[Self-Organization|self-organizing]] systems. Emergence and self-organization seem to be a contradiction to the second law of thermodynamics, which says that organization and order can not increase in isolated systems. They are possible because they usually happen in open systems, which extract information and order out of the environment and produce waste (import of order/information and export of disorder/entropy). The process of self-organization refers to the boundary between system and environment, the process of emergence involves the microscopic-macroscopic boundary between the individual and the collective group.

== Types and Forms ==

One can distinguish roughly between four types of emergence: (1) Simple/Nominal Emergence (2) Weak Emergence (3) Multiple Emergence (4) Strong Emergence. They can be distinguished by the different degree of predictability and the different types of roles.

=== Overview ===

{| border="0" cellpadding="5" width="100%"
|-
! bgcolor="#70b0e0" width="25%" align="left" | Type and Name
! bgcolor="#eedd90" width="25%" align="left" | Roles
! bgcolor="#bbbbbb" width="25%" align="left" | Frequency
! bgcolor="#77bb99" align="left" | Predictability
|-
| bgcolor="#80c0ff" valign="top" |
I Nominal or Intentional 
II Weak 
III Multiple 
IV Strong 

| bgcolor="#ffeea0" valign="top" |
Fixed 
Flexible 
Fluctating 
New World of Roles 

| bgcolor="#cccccc" valign="top" |
Abundant 
Frequent 
Common - Unusual 
Rare 

| bgcolor="#88ccaa" valign="top" |
totally predictable 
predictable in principle 
not predictable (chaotic) 
not predictable, even in principle 

|}

=== 1. Simple/Nominal Emergence (Type I) ===

The weakest possible sense is totally predictable, and has the strongest form of constraints: each component and element has a fixed and constant role, which is not allowed to change in the course of time. A system in form of a machine has for instance a function which is different from the function of the parts and components, but the overall function is well-known, and it only matches the planned and designed function. There are no unpredicted or unexpected behavior patterns.

{{SelfOrg}}

=== 2. Weak Emergence (Type II) ===

[[Image:Emergence.gif|left|Weak Emergence]] Weak emergence is the most common form of emergence related to swarms, flocks and other social groups. It describes emergence forms with simple feedback, which is predictable in principle, but not in every detail. The roles of the elements and agents are flexible (for example "transporter", "explorer", "defender" and "follower" in ant colonies. It is the classic form of emergence, which can be seen in the figure on the left side: coherent global structures appear and become visible on a higher level of organization through the local interaction of several autonomous agents. Top-down feedback from the group imposes in turn constraints on the local interactions. An example is a flock of Geese, which limits the possible movements of the individual birds. An important element is context-dependence: agents ajust their behavior and their role in the group according to the actual context and situation. Feedback from the group or the environment to the agent is possible through this form of context-dependent flexibility.

=== 3. Multiple Emergence (Type III) ===

Multiple emergence is a form of emergence with multiple positive and negative feedback loops. The behavior is not predictable, and can be chaotic. Completely new roles can appear, while old roles disappear.
A typical example for multiple emergence are bubbles are droplets.
M. Mitchell Waldrop says in his book "Complexity:
The Emerging Science at the Edge of Order and Chaos "
(Simon & Schuster, 1992) about the complex patterns of droplets :

"Imagine spilling a little water onto the surface of a
highly polished tray, (..) it beads up into a complex
pattern of droplets. And it does so because two countervailing
forces are at work. There is gravity, which tries to spread
out the water to make a very thin, flat film across the
whole surface. That's negative feedback. And there is surface
tension, the attraction of one water molecule to another,
which tries to pull the liquid together into compact globules.
That's positive feedback. It's the mix of the two forces
that produces the complex patterns of beads. Moreover, that
pattern is unique. Try the experiment again and you'll get
a completely different arrangement of droplets. Tiny
accidents of history - infinitesimal dust motes and
invisible irregularities in the surface of the tray -
get magnified by the positive feedback into major
differences in the outcome." (page 36)

=== 4. Strong Emergence (Type IV) ===

[[Image:Code.gif|left|Strong Emergence]] The strongest possible sense of emergence is related to supervenience, the weakest form of causal dependence. It is not predictable, even in principle, because it describes the appearance of a new [[Code|code]] or completely new [[System|system]] in a multi-level or multi-scale system with many levels. Combinatorial explosion renders any attempt of explaining emergent macroscopic, high-level phenomena in terms of microscopic low-level phenomena useless and futile. An intermediate or mesoscopic level often protects the macroscopic level from the microscopic level, i.e. the microscopic level is irrelevant to the behavior of the macroscopic level. Therefore strong emergence can be considered as crossing the barrier of relevance.

Strong emergence is very rare, and is normally the result of a long [[evolution|evolutionary process]], or the result of deliberate and intentional design. Classic examples for strong emergence are the appearance of life and living systems through the emergence of the genetic code, and the appearance of culture and cultural systems through the emergence of memetic code (i.e. linguistic codes and languages in general). In both cases, completely new evolutionary or [[Complex Adaptive System|complex adaptive systems]] appeared, which are subject to their own [[Evolution|evolution]].

Strong emergence can be distinguished from weak by the existence of a code which specifies a new
system in a system. Strong emergence is the emergence of a whole new system, with new building blocks and
interaction laws. The "strong" emergence of a system is identical or at least closely related to the simulation
or representation of a system through another system - simulation is the attempt to represent certain features
of the behavior of a system by the behavior of another system. The interface between the new and the old
system is described by a new code or language.

Characteristic signs for strong emergence are the existence of
*adaptors between two independent worlds
*codes and languages which define a correspondence between two independent worlds
*a multi-level or multi-scale system with many levels
*mesoscopic levels between the microscopic level of the individual cells, elements and agents, and the macroscopic level of the total system

=== Shadow Emergence (special case) ===

see [[Shadow_Emergence|Shadow Emergence]]

== Emergence and Evolution ==

[[Image:EmergenceEvolution.png|thumb|right|295px|The influence of self-organization and evolution in different emergence types]]

While [[Self-Organization|self-organization]] is frequently seen as the
cause for complexity in nature (since nobody "organizes" nature),
emergence is sometimes mistaken for the origin of jumps in complexity.
Yet neither self-organization nor emergence is responsible for overwhelming
complexity heights or sudden changes in complexity.
Simple forms of emergence (Type I, Type II and partially Type III) can
be considered as the result of [[Self-Organization|self-organization]].
This form is often temporary or instable: flocks dissolve,
schools of fish dissociate, and social groups disintegrate
after a while.

The real jumps in complexity are related to emergence in
[[Evolutionary System|evolutionary systems]].
[[Evolution|Evolution]] is still the main reason and the driving
force for the complexity and diversity which can be found in nature,
and neither the concept of self-organization nor the phenomenon
of emergence can really replace evolution or natural
selection. The evolution of "selfish genes" seems to be responsible
itself for all forms of sudden jumps in complexity in
history, i.e. the appearance of more and more complex
species or complex properties in the course of time.

Evolution is also responsible for all forms of "strong emergence" (Type IV),
in which whole new evolutionary systems appear
(associated with the emergence of a new code
which is used to create the new evolutionary system).
A new [[Code|code]] marks the limits between the
type I-III emergence due to forced extrinsic organization
and intrinsic [[Self-Organization|self-organization]],
and the type IV emergence due to evolution and deliberate
design of a new code. It also marks the limits of
[[Self-Organization|self-organization]] in general.

Sudden jumps in complexity due to evolution are often
related to fitness barriers. There are at least three different
ways to cope with fitness barriers in evolution (Type IIIb),
(1) bypass it, (2) tunnel through it, or (3) overcome it:

# to bypass through [[Exaptation|exaptation]]: explore a different direction and make a sudden side-leap
# to tunnel right through the barrier by borrowing [[Complexity|complexity]]
# to wait for a catastrophe, until the barrier is reduced through catastrophic events

== Examples ==

=== Classic Examples ===

[[Image:Langton.png|thumb|right|295px|Langton's Ant]]
Christopher '''Langton's Ant''' and John Von Neumann's
self-reproducing automata belong to the classic
examples of "emergence", besides '''Conway's Game of Life'''
from the field of ALife and '''Schelling's segregation model'''
from the social sciences.

Langton's Ant is sometimes considered as a [[Cellular_Automata|cellular automata]],
but it is more like an agent-based simulation with just
one agent: the ant that wanders around.
The rules for "Langton's Ant" are remarkably simple:
*If the ant is on a white cell it turns left 90 degrees and moves one unit forward
*If the ant is on a black cell it turns right 90 degrees and moves one unit forward
*As the ant moves to the next cell, the one that it is on changes color from white to black, or the reverse.

They can be formulated even simpler:
*The ant reverses the color of any cell it visits.
*When the ant visits a white square it turns left; when it visits a black square it turns right.

When the ant is started on an empty grid, these simple rules result
first in very comlex and chaotic pattern,
but after about ten thousand moves the ant suddenly
shows a repetitive pattern: it gets locked into a periood
or cycle of 104 steps and tries to build a broad diagonal
"highway", each time displacing the ant two pixels vertically
and horizontally. It is a good example for [[Stigmergy|stigmergy]]
and Type II emergence: the ant changes the environment
(the micro-macro direction), and the environment changes
in turn the behavior of the ant (the macro-micro feedback).

There are many applets for Langton's Ant on the net, for example [http://users.libero.it/acnard/ant.html] and
[http://www.math.ubc.ca/~cass/www/ant/ant.html].
[http://mathworld.wolfram.com/LangtonsAnt.html Mathworld] says it is a "4-state 2-dimensional Turing machine".

If a single agent which follows very simple rules
can produce such a complex behavior pattern,
then the behavior of a whole [[Multi-Agent System]]
with multiple agents and many different [[Agent|agent]]
types is of course much more complicated.

The self-reproducing automata from John Von Neumann
(and later from Edgar Codd) is more like a [[Cellular_Automata|cellular automata]]
and was deliberately constructed as a kind of
"self-reproducing machine", see [http://stud4.tuwien.ac.at/~e0125222/codd/].

=== Simple Examples ===

The simplest form of emergence is probably the following.
To build a single termite mound in an environment
consisting of randomly-scattered wood chips, a group
of termites each has only to follow one simple rule :

While wandering randomly
*if you find a chip then pick it up
*unless you're already carrying a chip in which case drop it

These simple rules lead to an automatic aggregation of chips and "heap formation". Several small heaps will start to emerge, but then the largest heap will grow at the expense of the smaller ones until there is only the larger one left, see [http://www.beart.org.uk/Emergent/index.htm] and
[http://ccl.northwestern.edu/netlogo/models/Termites].

=== Other Examples ===

The following phenomena are examples for emergent properties:

*a "who eats whom" foodweb is an emergent property of a complex ecosystem. It emerges as a stable, repeated pattern in a complex ecosystem

*a supply chain network is an emergent property of a complex economic system

*PageRank is an algorithm developed by Google to determine a web pages "inbound link ranking". The rank of each page is an emergent property. A Web page alone is hard to evaluate regarding its usefulness, correctness, and popularity, but taken together, all Web pages do give useful information, which can be extracted with the PageRank algorithm.

* a painting emerges from the unique combination of colored points, strokes and lines created by the painter,
similar to a book which arises from a unique combination of letters (all Type I)

=== Difficult Examples ===

Everything arises from atoms. Genes shape
life-forms. Brain chemicals shape behavior.
Assemblies of neurons shape consciousness
and thoughts. Just how exactly?

== Articles and Papers ==

Jochen Fromm's following preprints
* [http://arxiv.org/abs/nlin.AO/0506028 Types and Forms of Emergence]
* [http://arxiv.org/abs/nlin.AO/0509049 Ten Questions about Emergence]
* [http://arxiv.org/abs/nlin.AO/0601002 On Engineering and Emergence]

Shalizi's notebook entry on [http://cscs.umich.edu/~crshalizi/notebooks/emergent-properties.html Emergent Properties]

== Books ==
* John H. Holland, ''Emergence from chaos to order'' (1998) Oxford University Press, ISBN 0738201421
* Steven Johnson, ''Emergence'' (2002) Scribner, ISBN 0684868768
* Stephen Wolfram, ''[http://www.wolframscience.com/nksonline/toc.html A New Kind of Science]'' (2002), ISBN 1579550088.
* Jochen Fromm, ''[http://www.upress.uni-kassel.de/abstracts/3-89958-069-9.html The emergence of complexity]'' (2004) Kassel University Press, ISBN 3899580699
* Thomas C. Schelling, ''Micromotives and Macrobehavior'' (1978) W. W. Norton and Company
* Harold J. Morowitz, ''The Emergence of Everything: How the World Became Complex'' (2002) Oxford University Press, ISBN 019513513X
* Armand Delsemme, ''Our Cosmic Origins: From the Big Bang to the Emergence of Life and Intelligence'' (1998) Cambridge University Press
* John Maynard Smith and Eörs Szathmáry, ''The Major Transitions in Evolution'' (1997) Oxford University Press, ISBN 019850294X

==External links==

* [http://llk.media.mit.edu/projects/emergence/ Exploring Emergence]: An introduction to emergence using [[Conway's Game of Life]] from the [[MIT Media Lab]]
* [http://plato.stanford.edu/entries/properties-emergent/ Stanford Encyclopedia of Philosophy entry on Emergent Properties]
* Russ Abbott's [http://cs.calstatela.edu/~wiki/index.php/Courses/CS_461/Museum_of_unintended_consequences Museum of unintended consequences] in social systems and everyday life

[[Category:Basic Principles]]

Emergence

2008-09-18T16:44:40Z

213.218.25.117: /* Other Examples */

[[Image:Classic_View_of_Emergence.png|thumb|300px|The classic view of "emergence"]]

'''Emergence''' is a process which describes the appearance of emergent properties and phenomena. A property of a system is emergent, if it is not a property of any fundamental element. Composite entities can have properties that can not be found in the parts of the composition. In other words, emergence happens if "more is different", if there are properties of a group which can not be explained by the properties of the parts, entities and [[Agent|agents]] alone.

== Introduction ==

An emergent behavior is not imposed from the outside by a central controller or organizer,
it results solely from the interactions between the agents.
Emergence is a characteristic feature of many [[Complex System|complex]] and [[Self-Organization|self-organizing]] systems. Emergence and self-organization seem to be a contradiction to the second law of thermodynamics, which says that organization and order can not increase in isolated systems. They are possible because they usually happen in open systems, which extract information and order out of the environment and produce waste (import of order/information and export of disorder/entropy). The process of self-organization refers to the boundary between system and environment, the process of emergence involves the microscopic-macroscopic boundary between the individual and the collective group.

== Types and Forms ==

One can distinguish roughly between four types of emergence: (1) Simple/Nominal Emergence (2) Weak Emergence (3) Multiple Emergence (4) Strong Emergence. They can be distinguished by the different degree of predictability and the different types of roles.

=== Overview ===

{| border="0" cellpadding="5" width="100%"
|-
! bgcolor="#70b0e0" width="25%" align="left" | Type and Name
! bgcolor="#eedd90" width="25%" align="left" | Roles
! bgcolor="#bbbbbb" width="25%" align="left" | Frequency
! bgcolor="#77bb99" align="left" | Predictability
|-
| bgcolor="#80c0ff" valign="top" |
I Nominal or Intentional 
II Weak 
III Multiple 
IV Strong 

| bgcolor="#ffeea0" valign="top" |
Fixed 
Flexible 
Fluctating 
New World of Roles 

| bgcolor="#cccccc" valign="top" |
Abundant 
Frequent 
Common - Unusual 
Rare 

| bgcolor="#88ccaa" valign="top" |
totally predictable 
predictable in principle 
not predictable (chaotic) 
not predictable, even in principle 

|}

=== 1. Simple/Nominal Emergence (Type I) ===

The weakest possible sense is totally predictable, and has the strongest form of constraints: each component and element has a fixed and constant role, which is not allowed to change in the course of time. A system in form of a machine has for instance a function which is different from the function of the parts and components, but the overall function is well-known, and it only matches the planned and designed function. There are no unpredicted or unexpected behavior patterns.

{{SelfOrg}}

=== 2. Weak Emergence (Type II) ===

[[Image:Emergence.gif|left|Weak Emergence]] Weak emergence is the most common form of emergence related to swarms, flocks and other social groups. It describes emergence forms with simple feedback, which is predictable in principle, but not in every detail. The roles of the elements and agents are flexible (for example "transporter", "explorer", "defender" and "follower" in ant colonies. It is the classic form of emergence, which can be seen in the figure on the left side: coherent global structures appear and become visible on a higher level of organization through the local interaction of several autonomous agents. Top-down feedback from the group imposes in turn constraints on the local interactions. An example is a flock of Geese, which limits the possible movements of the individual birds. An important element is context-dependence: agents ajust their behavior and their role in the group according to the actual context and situation. Feedback from the group or the environment to the agent is possible through this form of context-dependent flexibility.

=== 3. Multiple Emergence (Type III) ===

Multiple emergence is a form of emergence with multiple positive and negative feedback loops. The behavior is not predictable, and can be chaotic. Completely new roles can appear, while old roles disappear.
A typical example for multiple emergence are bubbles are droplets.
M. Mitchell Waldrop says in his book "Complexity:
The Emerging Science at the Edge of Order and Chaos "
(Simon & Schuster, 1992) about the complex patterns of droplets :

"Imagine spilling a little water onto the surface of a
highly polished tray, (..) it beads up into a complex
pattern of droplets. And it does so because two countervailing
forces are at work. There is gravity, which tries to spread
out the water to make a very thin, flat film across the
whole surface. That's negative feedback. And there is surface
tension, the attraction of one water molecule to another,
which tries to pull the liquid together into compact globules.
That's positive feedback. It's the mix of the two forces
that produces the complex patterns of beads. Moreover, that
pattern is unique. Try the experiment again and you'll get
a completely different arrangement of droplets. Tiny
accidents of history - infinitesimal dust motes and
invisible irregularities in the surface of the tray -
get magnified by the positive feedback into major
differences in the outcome." (page 36)

=== 4. Strong Emergence (Type IV) ===

[[Image:Code.gif|left|Strong Emergence]] The strongest possible sense of emergence is related to supervenience, the weakest form of causal dependence. It is not predictable, even in principle, because it describes the appearance of a new [[Code|code]] or completely new [[System|system]] in a multi-level or multi-scale system with many levels. Combinatorial explosion renders any attempt of explaining emergent macroscopic, high-level phenomena in terms of microscopic low-level phenomena useless and futile. An intermediate or mesoscopic level often protects the macroscopic level from the microscopic level, i.e. the microscopic level is irrelevant to the behavior of the macroscopic level. Therefore strong emergence can be considered as crossing the barrier of relevance.

Strong emergence is very rare, and is normally the result of a long [[evolution|evolutionary process]], or the result of deliberate and intentional design. Classic examples for strong emergence are the appearance of life and living systems through the emergence of the genetic code, and the appearance of culture and cultural systems through the emergence of memetic code (i.e. linguistic codes and languages in general). In both cases, completely new evolutionary or [[Complex Adaptive System|complex adaptive systems]] appeared, which are subject to their own [[Evolution|evolution]].

Strong emergence can be distinguished from weak by the existence of a code which specifies a new
system in a system. Strong emergence is the emergence of a whole new system, with new building blocks and
interaction laws. The "strong" emergence of a system is identical or at least closely related to the simulation
or representation of a system through another system - simulation is the attempt to represent certain features
of the behavior of a system by the behavior of another system. The interface between the new and the old
system is described by a new code or language.

Characteristic signs for strong emergence are the existence of
*adaptors between two independent worlds
*codes and languages which define a correspondence between two independent worlds
*a multi-level or multi-scale system with many levels
*mesoscopic levels between the microscopic level of the individual cells, elements and agents, and the macroscopic level of the total system

=== Shadow Emergence (special case) ===

see [[Shadow_Emergence|Shadow Emergence]]

== Emergence and Evolution ==

[[Image:EmergenceEvolution.png|thumb|right|295px|The influence of self-organization and evolution in different emergence types]]

While [[Self-Organization|self-organization]] is frequently seen as the
cause for complexity in nature (since nobody "organizes" nature),
emergence is sometimes mistaken for the origin of jumps in complexity.
Yet neither self-organization nor emergence is responsible for overwhelming
complexity heights or sudden changes in complexity.
Simple forms of emergence (Type I, Type II and partially Type III) can
be considered as the result of [[Self-Organization|self-organization]].
This form is often temporary or instable: flocks dissolve,
schools of fish dissociate, and social groups disintegrate
after a while.

The real jumps in complexity are related to emergence in
[[Evolutionary System|evolutionary systems]].
[[Evolution|Evolution]] is still the main reason and the driving
force for the complexity and diversity which can be found in nature,
and neither the concept of self-organization nor the phenomenon
of emergence can really replace evolution or natural
selection. The evolution of "selfish genes" seems to be responsible
itself for all forms of sudden jumps in complexity in
history, i.e. the appearance of more and more complex
species or complex properties in the course of time.

Evolution is also responsible for all forms of "strong emergence" (Type IV),
in which whole new evolutionary systems appear
(associated with the emergence of a new code
which is used to create the new evolutionary system).
A new [[Code|code]] marks the limits between the
type I-III emergence due to forced extrinsic organization
and intrinsic [[Self-Organization|self-organization]],
and the type IV emergence due to evolution and deliberate
design of a new code. It also marks the limits of
[[Self-Organization|self-organization]] in general.

Sudden jumps in complexity due to evolution are often
related to fitness barriers. There are at least three different
ways to cope with fitness barriers in evolution (Type IIIb),
(1) bypass it, (2) tunnel through it, or (3) overcome it:

# to bypass through [[Exaptation|exaptation]]: explore a different direction and make a sudden side-leap
# to tunnel right through the barrier by borrowing [[Complexity|complexity]]
# to wait for a catastrophe, until the barrier is reduced through catastrophic events

== Examples ==

=== Classic Examples ===

[[Image:Langton.png|thumb|right|295px|Langton's Ant]]
Christopher '''Langton's Ant''' and John Von Neumann's
self-reproducing automata belong to the classic
examples of "emergence", besides '''Conway's Game of Life'''
from the field of ALife and '''Schelling's segregation model'''
from the social sciences.

Langton's Ant is sometimes considered as a [[Cellular_Automata|cellular automata]],
but it is more like an agent-based simulation with just
one agent: the ant that wanders around.
The rules for "Langton's Ant" are remarkably simple:
*If the ant is on a white cell it turns left 90 degrees and moves one unit forward
*If the ant is on a black cell it turns right 90 degrees and moves one unit forward
*As the ant moves to the next cell, the one that it is on changes color from white to black, or the reverse.

They can be formulated even simpler:
*The ant reverses the color of any cell it visits.
*When the ant visits a white square it turns left; when it visits a black square it turns right.

When the ant is started on an empty grid, these simple rules result
first in very comlex and chaotic pattern,
but after about ten thousand moves the ant suddenly
shows a repetitive pattern: it gets locked into a periood
or cycle of 104 steps and tries to build a broad diagonal
"highway", each time displacing the ant two pixels vertically
and horizontally. It is a good example for [[Stigmergy|stigmergy]]
and Type II emergence: the ant changes the environment
(the micro-macro direction), and the environment changes
in turn the behavior of the ant (the macro-micro feedback).

There are many applets for Langton's Ant on the net, for example [http://users.libero.it/acnard/ant.html] and
[http://www.math.ubc.ca/~cass/www/ant/ant.html].
[http://mathworld.wolfram.com/LangtonsAnt.html Mathworld] says it is a "4-state 2-dimensional Turing machine".

If a single agent which follows very simple rules
can produce such a complex behavior pattern,
then the behavior of a whole [[Multi-Agent System]]
with multiple agents and many different [[Agent|agent]]
types is of course much more complicated.

The self-reproducing automata from John Von Neumann
(and later from Edgar Codd) is more like a [[Cellular_Automata|cellular automata]]
and was deliberately constructed as a kind of
"self-reproducing machine", see [http://stud4.tuwien.ac.at/~e0125222/codd/].

=== Simple Examples ===

The simplest form of emergence is probably the following.
To build a single termite mound in an environment
consisting of randomly-scattered wood chips, a group
of termites each has only to follow one simple rule :

While wandering randomly
*if you find a chip then pick it up
*unless you're already carrying a chip in which case drop it

These simple rules lead to an automatic aggregation of chips and "heap formation". Several small heaps will start to emerge, but then the largest heap will grow at the expense of the smaller ones until there is only the larger one left, see [http://www.beart.org.uk/Emergent/index.htm] and
[http://ccl.northwestern.edu/netlogo/models/Termites].

=== Other Examples ===

The following phenomena are examples for emergent properties:

*a "who eats whom" foodweb is an emergent property of a complex ecosystem. It emerges as a stable, repeated pattern in a complex ecosystem

*a supply chain network is an emergent property of a complex economic system

*PageRank is an algorithm developed by Google to determine a web pages "inbound link ranking". The rank of each page is an emergent property. A Web page alone is hard to evaluate regarding its usefulness, correctness, and popularity, but taken together, all Web pages do give useful information, which can be extracted with the PageRank algorithm.

*a painting emerges from the unique combination of colored points, strokes and lines created by the painter.

=== Difficult Examples ===

Everything arises from atoms. Genes shape
life-forms. Brain chemicals shape behavior.
Assemblies of neurons shape consciousness
and thoughts. Just how exactly?

== Articles and Papers ==

Jochen Fromm's following preprints
* [http://arxiv.org/abs/nlin.AO/0506028 Types and Forms of Emergence]
* [http://arxiv.org/abs/nlin.AO/0509049 Ten Questions about Emergence]
* [http://arxiv.org/abs/nlin.AO/0601002 On Engineering and Emergence]

Shalizi's notebook entry on [http://cscs.umich.edu/~crshalizi/notebooks/emergent-properties.html Emergent Properties]

== Books ==
* John H. Holland, ''Emergence from chaos to order'' (1998) Oxford University Press, ISBN 0738201421
* Steven Johnson, ''Emergence'' (2002) Scribner, ISBN 0684868768
* Stephen Wolfram, ''[http://www.wolframscience.com/nksonline/toc.html A New Kind of Science]'' (2002), ISBN 1579550088.
* Jochen Fromm, ''[http://www.upress.uni-kassel.de/abstracts/3-89958-069-9.html The emergence of complexity]'' (2004) Kassel University Press, ISBN 3899580699
* Thomas C. Schelling, ''Micromotives and Macrobehavior'' (1978) W. W. Norton and Company
* Harold J. Morowitz, ''The Emergence of Everything: How the World Became Complex'' (2002) Oxford University Press, ISBN 019513513X
* Armand Delsemme, ''Our Cosmic Origins: From the Big Bang to the Emergence of Life and Intelligence'' (1998) Cambridge University Press
* John Maynard Smith and Eörs Szathmáry, ''The Major Transitions in Evolution'' (1997) Oxford University Press, ISBN 019850294X

==External links==

* [http://llk.media.mit.edu/projects/emergence/ Exploring Emergence]: An introduction to emergence using [[Conway's Game of Life]] from the [[MIT Media Lab]]
* [http://plato.stanford.edu/entries/properties-emergent/ Stanford Encyclopedia of Philosophy entry on Emergent Properties]
* Russ Abbott's [http://cs.calstatela.edu/~wiki/index.php/Courses/CS_461/Museum_of_unintended_consequences Museum of unintended consequences] in social systems and everyday life

[[Category:Basic Principles]]