Abstract
We deal with a multiagent system where the agents decide with whom to cooperate on the basis of multiple criteria. The system models these criteria with the help of propositions. The agents rate the propositions with value-vectors to model different degrees of agreement with the propositions. In the system the agents adapt their values via different strategies. We will examine the influence of the number of propositions and the influence of different adaptation strategies for the performance of the system in a job and task allocation domain. The results show that high levels of cooperation can be reached through self-adapting agents.
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Eberling, M., Büning, H.K. (2010). Self-adaptation Strategies to Favor Cooperation. In: Jędrzejowicz, P., Nguyen, N.T., Howlet, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2010. Lecture Notes in Computer Science(), vol 6070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13480-7_24
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DOI: https://doi.org/10.1007/978-3-642-13480-7_24
Publisher Name: Springer, Berlin, Heidelberg
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