Emergence of a Multi-Agent Architecture and New Tactics for the Ant Colony Food Foraging Problem Using Genetic Programming
Forrest H Bennett · The MIT Press eBooks · 1996
Previous work in multi-agent systems has required the human designer to make up-front decisions about the multi-agent architecture, including the number of agents to employ and the specific tasks to be performedby each agent. This paper describes the automatic evolution of these decisions during a run of genetic programming using architecture-altering operations.Genetic programming is extended to the discovery of multi-agent solutions for a central-place foraging problem for an ant colony. In this problem each individual ant is controlled by a set of agents, where agent is used in the sense of Minsky's Society of Mind.Two new tactics for the central-place food foraging problem that were discovered by genetic programming are presented in this paper.Genetic programming was able to evolve time-efficient solutions to this problem by distributing the functions and terminals across successively more agents in such a way as to reduce the maximum number of functions executed per agent. The other source of time-efficiency in the evolved solution was the cooperation that emerged among the ants in the ant colony.