Abstract
The paper deals with field-based coordination of agent team in which the continental divide game is applied as a coordination mechanism. The agent team consists of self-interested mobile intelligent agents whose behaviour is modelled using coordination policies based on adaptive learning algorithms. Three types of learning algorithms have been used: three parameter Roth-Erev algorithm, stateless Q-learning algorithm, and experience-weighted attraction algorithm. The coordination policies are analyzed by replicator dynamics from evolutionary game theory. A case study describing performance evaluation of coordination policies according to the analysis is considered.
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Trzec, K., Lovrek, I. (2007). Field-Based Coordination of Mobile Intelligent Agents: An Evolutionary Game Theoretic Analysis. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_25
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DOI: https://doi.org/10.1007/978-3-540-74819-9_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
Online ISBN: 978-3-540-74819-9
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