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Coevolution of Heterogeneous MultiRobot Teams (2010)
| Venue: | Proceedings of the Genetic and Evolutionary Computation Conference |
| Citations: | 10 - 9 self |
BibTeX
@INPROCEEDINGS{Knudson10coevolutionof,
author = {Matt Knudson and Kagan Tumer},
title = {Coevolution of Heterogeneous MultiRobot Teams},
booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference},
year = {2010},
pages = {127--134}
}
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Abstract
Evolving multiple robots so that each robot acting independently can contribute to the maximization of a system level objective presents significant scientific challenges. For example, evolving multiple robots to maximize aggregate information in exploration domains (e.g., planetary exploration, search and rescue) requires coordination, which in turn requires the careful design of the evaluation functions. Additionally, where communication among robots is expensive (e.g., limited power or computation), the coordination must be achieved passively, without robots explicitly informing others of their states/intended actions. Coevolving robots in these situations is a potential solution to producing coordinated behavior, where the robots are coupled through their evaluation functions. In this work, we investigate coevolution in three types of domains: (i) where precisely n homogeneous robots need to perform a task; (ii) where n is the optimal number of homogeneous robots for the task; and (iii) where n is the optimal number of heterogeneous robots for the task. Our results show that coevolving robots with evaluation functions that are locally aligned with the system evaluation significantly improve performance over robots evolving using the system evaluation function directly, particularly in dynamic environments.
Keyphrases
heterogeneous multirobot team evaluation function homogeneous robot optimal number multiple robot system evaluation function aggregate information careful design planetary exploration heterogeneous robot limited power system evaluation dynamic environment coordinated behavior potential solution exploration domain
