Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks


Claes, Daniel, Robbel, Philipp, Oliehoek, Frans ORCID: 0000-0003-4372-5055, Tuyls, Karl, Hennes, Daniel and Van Der Hoek, Wiebe (2015) Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015). pp. 881-890.

This is the latest version of this item.

[img] Text
Claes15AAMAS.pdf - Unspecified
Download (392kB)

Abstract

Although multi-robot systems have received substantial re- search attention in recent years, multi-robot coordination still remains a difficult task. Especially, when dealing with spatially distributed tasks and many robots, central control quickly becomes infeasible due to the exponential explosion in the number of joint actions and states. We propose a gen- eral algorithm that allows for distributed control, that over- comes the exponential growth in the number of joint actions by aggregating the effect of other agents in the system into a probabilistic model, called subjective approximations, and then choosing the best response. We show for a multi-robot grid world how the algorithm can be implemented in the well studied Multiagent Markov Decision Process framework, as a sub-class called spatial task allocation problems (SPAT- APs). In this framework, we show how to tackle SPATAPs using online, distributed planning by combining subjective agent approximations with restriction of attention to current tasks in the world. An empirical evaluation shows that the combination of both strategies allows to scale to very large problems, while providing near-optimal solutions.

Item Type: Article
Depositing User: Symplectic Admin
Date Deposited: 08 Apr 2016 11:05
Last Modified: 16 Dec 2022 04:43
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3000363

Available Versions of this Item

CORE (COnnecting REpositories)