Multiagent Systems: Lessons From Social Insects and Collective Robotics

Adaptation, Coevolution, and Learning in Multiagent Systems

Volume

Papers from the 1996 AAAI Spring Symposium

Contents

Multiagent systems used in the AI community are typically knowledge based, consisting of heterogeneous unembodied agents carrying out explicitly assigned tasks, and communicating via symbols. In contrast, many extremely competent natural collective systems of multiple agents (e.g. social insects) are not knowledge based, and are predominantly homogeneous and embodied; agents have no explicit task assignment, and do not communicate symbolically. A common method of control used in such collective systems is stigmergy, the production of a certain behaviour in agents as a consequence of the effects produced in the local environment by previous behaviour. This paper shows how stigmergy is used successfully in a collective robot system modelled on ants, and considers the possibility of extending the use of stigmergy and other forms of collective control to conventional multiagent or hybrid systems.