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- Publisher
- Association for Computing Machinery
- Copyright
- Copyright © 2006 by ACM Inc.
- ISSN
- 1556-4665
- DOI
- 10.1145/1152934.1152936
- Publisher site
- See Article on Publisher Site
Abstract
In this article, we analyze the behavior of a group of robots involved in an object retrieval task. The robots' control system is inspired by a model of ants' foraging. This model emphasizes the role of learning in the individual. Individuals adapt to the environment using only locally available information. We show that a simple parameter adaptation is an effective way to improve the efficiency of the group and that it brings forth division of labor between the members of the group. Moreover, robots that are best at retrieving have a higher probability of becoming active retrievers. This selection of the best members does not use any explicit representation of individual capabilities. We analyze this system and point out its strengths and its weaknesses.
Journal
ACM Transactions on Autonomous and Adaptive Systems (TAAS) – Association for Computing Machinery
Published: Sep 1, 2006