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ATAL
2004
Springer

Analysis of a Stochastic Model of Adaptive Task Allocation in Robots

9 years 6 months ago
Analysis of a Stochastic Model of Adaptive Task Allocation in Robots
Adaptation is an essential requirement for self–organizing multi–agent systems functioning in unknown dynamic environments. Adaptation allows agents, e.g., robots, to change their actions in response to environmental changes or actions of other agents in order to improve overall system performance, and remain robust even while a sizeable fraction of agents fails. In this paper we present and study a simple model of adaptation for the task allocation problem in a multi–robot system. In our model robots have to choose between two types of tasks, and the goal is to achieve desired task division without any explicit communication between robots. Robots estimate the state of the environment from repeated local observations and decide what task to choose based on these observations. We model robots and observations as stochastic processes and study the dynamics of individual robots and the collective behavior. We validate our analysis with numerical simulations.
Aram Galstyan, Kristina Lerman
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where ATAL
Authors Aram Galstyan, Kristina Lerman
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