On the evolution of homogeneous two-robot teams: clonal versus aclonal approaches

Tuci, Elio and Trianni, Vito (2014) On the evolution of homogeneous two-robot teams: clonal versus aclonal approaches. Neural Computing and Applications, 25 (5) . pp. 1063-1076. ISSN 0941-0643 [Article] (doi:10.1007/s00521-014-1594-0)

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This study compares two different evolutionary approaches (clonal and aclonal) to the design of homogeneous two-robot teams (i.e. teams of morphologically identical agents with identical controllers) in a task that requires the agents to specialise to different roles. The two approaches differ mainly in the way teams are formed during evolution. In the clonal approach, a team is formed from a single genotype within one population of genotypes. In the aclonal approach, a team is formed from multiple genotypes within one population of genotypes. In both cases, the goal is the synthesis of individual generalist controllers capable of integrating role execution and role allocation mechanisms for a team of homogeneous robots. Our results diverge from those illustrated in a similar comparative study, which supports the superiority of the aclonal versus the clonal approach. We question this result and its theoretical underpinning, and we bring new empirical evidence showing that the clonal outperforms the aclonal approach in generating homogeneous teams required to dynamically specialise for the benefit of the team. The results of our study suggest that task-specific elements influence the evolutionary dynamics more than the genetic relatedness of the team members. We conclude that the appropriateness of the clonal approach for role allocation scenarios is mainly determined by the specificity of the collective task, including the evaluation function, rather than by the way in which the solutions are evaluated during evolution.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 21937
Notes on copyright: The final publication is available at Springer via http://dx.doi.org/10.1007/s00521-014-1594-0
Depositing User: Elio Tuci
Date Deposited: 13 Jun 2017 14:31
Last Modified: 29 Nov 2022 23:21
URI: https://eprints.mdx.ac.uk/id/eprint/21937

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