This paper investigates the possibility of evolving communication in a multi-agent system (MAS) and a software simulation has been developed for this purpose. Agents in this system are controlled by an artificial neural network of the standard feed-forward type. The agent behaviour is evolved by modifying the connection weights using a steady-state genetic algorithm. After a discussion of the theory behind the evolution of communication some preliminary results are presented that demonstrate that even in relatively simple environments coordinated group behaviour can evolve consistently. Possible extensions to the simulation system are outlined that should promote the evolution of communication between agents.
|Title of host publication||Proceedings of the Third International Conference on the Evolution of Language (EvoLang 2000)|
|Publication status||Published - 2000|