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Adapting populations of agents

De Wilde, Philippe, Chli, Maria, Correia, L., Ribeiro, R., Mariano, P., Abramov, V., Goossenaerts, J. (2003) Adapting populations of agents. In: Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). Adaptive Agents and Multi-Agent Systems: Adaptation and Multi-Agent Learning - 3rd Symposium on Adaptive Agents and Multi-Agent Systems, AAMAS 2003. 2636. pp. 110-124. Springer ISBN 978-3-540-40068-4. E-ISBN 978-3-540-44826-6. (doi:10.1007/3-540-44826-8_7) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:58047)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://doi-org.chain.kent.ac.uk/10.1007/3-540-448...

Abstract

We control a population of interacting software agents. The agents have a strategy, and receive a payoff for executing that strategy. Unsuccessful agents become extinct. We investigate the repercussions of maintaining a diversity of agents. There is often no economic rationale for this. If maintaining diversity is to be successful, i.e. without lowering too much the payoff for the non-endangered strategies, it has to go on forever, because the non-endangered strategies still get a good payoff, so that they continue to thrive, and continue to endanger the endangered strategies. This is not sustainable if the number of endangered ones is of the same order as the number of non-endangered ones. We also discuss niches, islands. Finally, we combine learning as adaptation of individual agents with learning via selection in a population. © Springer-Verlag Berlin Heidelberg 2003.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1007/3-540-44826-8_7
Uncontrolled keywords: Adaptive systems; Computer simulation; Decision making; Game theory; Learning systems; Population statistics; Set theory; Software agents, Evolutionary game theory; Genetic codes; Population dynamics; Replicator dynamics, Software agents; Multi agent systems, Individual agent; Interacting softwares
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Philippe De Wilde
Date Deposited: 19 Dec 2022 15:50 UTC
Last Modified: 13 Jan 2023 09:42 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58047 (The current URI for this page, for reference purposes)

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