Swarm intelligence/Artificial Intelligence

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Artificial Intelligence: The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems.[1].

Algorithmic implementations of SI systems consist typically of a population of ("simple") agents or boids interacting locally with one another and with their environment. The diversity of individuals is reduces in complexity to study similarities inspired from nature, especially biological systems. The agents in the SI system follow in this case very simple rules. The algorithmic implementation the reduce the complexity of individuals to study, how even without a centralized control structure for the individual could lead to the emergence of "intelligent" global behavior, unknown to the individual agents. Examples in natural systems of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling. The definition of swarm intelligence is still not quite clear. In principle, it should be a multi-agent system that has self-organized behaviour that shows some intelligent behaviour.

The application of swarm principles to robots is called swarm robotics, while 'swarm intelligence' refers to the more general set of algorithms. 'Swarm prediction' has been used in the context of forecasting problems.

Learning Task[edit | edit source]

  • A neural netowrk consist of neurons (single cells) that are connected in a network via synapses. The communicate over the network with electro-chemical signal processing. Explain similarities between swarm intelligence and emergence of intelligence in out brain.

References[edit | edit source]

  1. 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)