Collective Complexity out of Individual Simplicity

Abstract

The concept of Swarm Intelligence (SI) was first introduced by Gerardo Beni, Suzanne
\nHackwood, and Jing Wang in 1989 when they were investigating the properties of
\nsimulated, self-organizing agents in the framework of cellular robotic systems [1]. Eric
\nBonabeau, Marco Dorigo, and Guy Theraulaz extend the restrictive context of this
\nearly work to include “any attempt to design algorithms or distributed problem-solving
\ndevices inspired by the collective behavior of social insect colonies,” such as ants,
\ntermites, bees, wasps, “and other animal societies.” The abilities of such systems appear
\nto transcend the abilities of the constituent individuals. In most biological cases studied
\nso far, robust and capable high-level group behavior has been found to be mediated
\nby nothing more than a small set of simple low-level interactions between individuals,
\nand between individuals and the environment. The SI approach, therefore, emphasizes
\nparallelism, distributedness, and exploitation of direct (agent-to-agent) or indirect (via
\nthe environment) local interactions among relatively simple agents.