Swarm intelligence

Swarm intelligence (SI) is artificial intelligence based on the collective behavior of decentralized, self-organized systems. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems [ Beni, G., Wang, J. Swarm Intelligence in Cellular Robotic Systems, Proceed. NATO Advanced Workshop on Robots and Biological Systems, Tuscany, Italy, June 26–30 (1989)] .

SI systems are typically made up of a population of simple agents interacting locally with one another and with their environment. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local interactions between such agents lead to the emergence of complex global behavior. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling.

The application of swarm principles to robots is called swarm robotics, while 'swarm intelligence' refers to the more general set of algorithms.

Example algorithms

Ant colony optimization

Ant colony optimization is a class of optimization algorithms modeled on the actions of an ant colony. Artificial 'ants' - simulation agents - locate optimal solutions by moving through a parameter space representing all possible solutions. Real ants lay down pheromones directing each other to resources while exploring their environment. The simulated 'ants' similarly record their positions and the quality of their solutions, so that in later simulation iterations more ants locate better solutions. [Ant Colony Optimization by Marco Dorigo and Thomas Stützle, MIT Press, 2004. ISBN 0-262-04219-3] One variation on this approach is the bees algorithm, which is more analogous to the foraging patterns of the honey bee.

Particle swarm optimization

Particle swarm optimization or PSO is a global optimization algorithm for dealing with problems in which a best solution can be represented as a point or surface in an n-dimensional space. Hypotheses are plotted in this space and seeded with an initial velocity, as well as a communication channel between the particles [ [http://springerlink.com/openurl.asp?genre=article&id=doi:10.1023/A:1016568309421 Recent Approaches to Global Optimization Problems Through Particle Swarm Optimization] , by Parsopoulos, K.E., Vrahatis, M.N., Natural Computing, 1 (2-3), pp. 235-306, 2002.] [ [http://www.iste.co.uk/?searchtext=clerc&ACTION=Search&cat=&ACTION=Search Particle Swarm Optimization] by Maurice Clerc, ISTE, ISBN 1-905209-04-5, 2006.] . Particles then move through the solution space, and are evaluated according to some fitness criterion after each timestep. Over time, particles are accelerated towards those particles within their communication grouping which have better fitness values. The main advantage of such an approach over other global minimization strategies such as simulated annealing is that the large number of members that make up the particle swarm make the technique impressively resilient to the problem of local minima.

tochastic diffusion search

Stochastic Diffusion Search or SDS is an agent based on probabilistic global search and optimization technique best suited to problems where the objective function can be decomposed into multiple independent partial-functions. Each agent maintains a hypothesis which is iteratively tested by evaluating a randomly selected partial objective function parameterised by the agent's current hypothesis. In the standard version of SDS such partial function evaluations are binary resulting in each agent becoming active or inactive. Information on hypotheses is diffused across the population via inter-agent communication. Unlike the stigmergic communication used in ACO, in SDS agents communicate hypotheses via a one-to-one communication strategy analogous to the tandem running procedure observed in some species of ant. A positive feedback mechanism ensures that, over time, a population of agents stabilise around the global-best solution. SDS is both an efficient and robust search and optimisation algorithm, which has been extensively mathematically described.

Applications

Swarm Intelligence-based techniques can be used in a number of applications. The U.S. military is investigating swarm techniques for controlling unmanned vehicles. The European Space Agency is thinking about an orbital swarm for self assembly and interferometry. NASA is investigating the use of swarm technology for planetary mapping. A 1992 paper by M. Anthony Lewis and George A. Bekey [Lewis, M. Anthony, and Bekey, George A. The Behavioral Self-Organization of Nanorobots Using Local Rules. Proceedings of the 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems.] discusses the possibility of using swarm intelligence to control nanobots within the body for the purpose of killing cancer tumors. Artists are using swarm technology as a means of creating complex interactive systems or simulating crowds. Tim Burton's "Batman Returns" was the first movie to make use of swarm technology for rendering, realistically depicting the movements of a group of penguins using the Boids system. The "Lord of the Rings" film trilogy made use of similar technology, known as Massive, during battle scenes. Swarm technology is particularly attractive because it is cheap, robust, and simple.

The inherent intelligence of swarms has inspired many social and political philosophers, in that the collective movements of an aggregate often derive from independent decision making on the part of a single individual. A common example is how the unaided decision of a person in a crowd to start clapping will often encourage others to follow suit, culminating in widespread applause. Such knowledge, an individualist advocate might argue, should encourage individual decision making (however mundane) as an effective tool in bringing about widespread social change.

The use of Swarm Intelligence in Telecommunication Networks has also been researched, in the form of Ant Based Routing. This was pioneered separately by Dorigo et al and Hewlett Packard in the mid-1990s, with a number of variations since. Basically this uses a probabilistic routing table rewarding/reinforcing the route successfully traversed by each "ant" (a small control packet) which flood the network. Reinforcement of the route in the forwards, reverse direction and both simultaneously have been researched: backwards reinforcement requires a symmetric network and couples the two directions together; forwards reinforcement rewards a route before the outcome is known (but then you pay for the cinema before you know how good the film is). As the system behaves stochastically and is therefore lacking repeatability, there are large hurdles to commercial deployment.

References in popular culture

Swarm intelligence-related concepts and references can be found throughout popular culture, frequently as some form of collective intelligence or group mind involving far more agents than used in current applications.

* "Prey", by Michael Crichton deals with the danger of nano-robots escaping from human control and developing a swarm intelligence.
* "Wyrm", a novel by Mark Fabi deals with a virus developing emergent intelligence on the Internet
* "Swarm", a short story by Bruce Sterling about a mission undertaken by a faction of humans, to understand and exploit a space-faring swarm intelligence.
* "Hacker and the ants", a book by Rudy Rucker on AI ants within a virtual environment
* Ygramul, the Many - an intelligent being consisting of a swarm of many wasp-like insects, a character in the novel "The Neverending Story" written by Michael Ende. Ygramul is also mentioned in a scientific paper [http://wwwisg.cs.uni-magdeburg.de/games/veranstaltungsarchiv/2003_ss/csii/boids.pdf#search=%22Ygramul%20the%20Many%22 Flocks, Herds, and Schools] written by Knut Hartmann (Computer Graphics and Interactive Systems Otto-von-Guericke-University of Magdeburg).
* "Allucination", a novel by Isaac Asimov about an alien insect-like swarm, capable of organization and provided with a sort of swarm intelligence.
* In Olaf Stapledon's 1931 science fiction novel "Last and First Men" there is an episode in which Earth is invaded by a swarm intelligence from Mars of tiny individual cells that communicate with each other by radio waves and that look like green fog.
* "The Invincible" science fiction novel by Stanislaw Lem where a human spaceship finds an intelligent behavior in a flock of small particles that were able to defend themselves against what they found as a menace.
* In The Matrix movies, the robotic sentinels exhibit signs of swarm intelligence. Additionally, in "The Matrix Revolutions", a machine called the "Deus Ex Machina" uses a swarm of thousands of insect-like robots to form a giant animated face.
* In the anime, "Soukou no Strain", unmanned robotic drones known as TUMORS display signs of swarm intelligence as they attack in groups.

Notable Researchers

* Gerardo Beni
* Marco Dorigo
* Luca Maria Gambardella
* Russell C. Eberhart
* James Kennedy
* Robert J. Marks II
* Craig Reynolds
* Ken Rinaldo
* Jing Wang
* Alcherio Martinoli

ee also

* AgentSheets - A visual programming authoring and visualization tool to build swams based on Antiobjects
* Bees algorithm
* Boids - A flocking simulation produced by Craig Reynolds
* Collective intelligence
* Cellular automaton
* Differential evolution
* Emergence
* Evolutionary computation
* Flocking (behavior)
* GPACSystem
* Harmony search
* Herd behavior
* Swarm robotics
* SwisTrack - A tracking tool for multi-unit biological and artificial systems
* Multi-agent system

References

* M. Dorigo & M. Birattari, 2007. [http://www.scholarpedia.org/article/Swarm_intelligence "Swarm Intelligence"] . Scholarpedia.

External links

*"Swarm Intelligence: From Natural to Artificial Systems" by Eric Bonabeau, Marco Dorigo and Guy Theraulaz. (1999) ISBN 0-19-513159-2, [http://bibnetwiki.org/wiki/Swarm_Intelligence complete bibliography]
*"Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds" by Mitchel Resnick. ISBN 0-262-18162-2
*"Swarm Intelligence" by James Kennedy and Russell C. Eberhart. ISBN 1-55860-595-9
*" [http://si.cs.up.ac.za Fundamentals of Computational Swarm Intelligence] " by Andries Engelbrecht. Wiley & Sons. ISBN 0-470-09191-6
*" [http://www.iste.co.uk/index.php?f=a&ACTION=View&id=194 Nanocomputers and Swarm Intelligence] " by Jean-Baptiste Waldner, ISTE, ISBN 9781847040022, 2007.
*Citation | last=Miller | first=Peter | title=Swarm Theory | magazine=National Geographic Magazine | date=July 2007 | url=http://www7.nationalgeographic.com/ngm/0707/feature5/
*"Swarms and Swarm Intelligence" by Michael G. Hinchey, Roy Sterritt, and Chris Rouff, [http://www.computer.org/portal/site/computer/menuitem.5d61c1d591162e4b0ef1bd108bcd45f3/index.jsp?&pName=computer_level1_article&TheCat=1065&path=computer/homepage/April07&file=softtech.xml&xsl=article.xsl Article at IEEE Computer Society]
* [http://www.nytimes.com/2007/11/13/science/13traff.html?ei=5087&em=&en=2770422853e9f63e&ex=1195102800&pagewanted=print - "From Ants to People: an Instinct to Swarm" - NY Times, 11-13-07]