A Model of Adaptation in Collaborative Multi-Agent Systems

Abstract

Adaptation is an essential requirement for autonomous agent systems functioning in uncertain dynamic environments. Adaptation allows agents to change their behavior in order to improve the overall sys tem performance. We describe a general mechanism for adaptation in multi-agent systems in which agents modify their behavior in response to changes in the environment or actions of other agents. The agents estimate the global state of the system from local observations and adjust their actions accordingly. We derive a mathematical model that describes the collective behavior of such adaptive systems. The model, consisting of coupled rate equations, governs how the collective behavior changes in time. We apply the model to study collaboration in a group of mobile robots. The system we study is an adaptive version of the collaborative stick pulling in a group of robots examined in detail in earlier works (Ijspeert, Martinoli, Billard, & Gambardela, 2001; Lerman, Galstyan, Martinoli, & Ijspeert, 2001). In adaptive stick pulling, robots estimate the number of robots and sticks in the system and adjust their individual behavior so as to improve collective performance. We solve the mathematical model and show that adaptation improves collective performance for all parameter values.