Abstract
In this paper, we introduce an asynchronous version of the well-known pursuit game. The validity of past results on the synchronous version of the pursuit game is verified in this new setting by considering five kinds of prey: Still prey, randomly moving prey, avoiding prey, linear prey, and linear prey with switching behavior. Genetic programming is used to evolve teams of predators whose capture rates are compared to that of a greedy strategy. Task assignment is used as an explicit means of coordination in the evolved teams of predators. We conclude that evolved teams with explicit coordination outperform greedy non-cooperative strategies when more competent prey is faced.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Axelrod, R.: The Evolution of Strategies in the Iterated Prisoner’s Dilemma. In: Davis, L. (ed.) Genetic Algorithms and Simulated Annealing, Morgan Kaufman, San Francisco (1987)
Benda, M., Jagannathan, V., Dodhiawalla, R.: On optimal cooperation of knowledge sources. Technical Report BCS-G2010-28, Boeing AI Center, Boeing Computer Services, Bellevue WA (August 1985)
Haynes, T., Sen, S.: Learning Cases to Resolve Conflicts and Improve Group Behavior. In: Working Notes of the AAAI 1996 Workshop on Agent Modeling (1996)
Haynes, T., Sen, S.: Evolving Behavioral Strategies in Predators and Prey. In: IJCAI 1995 Workshop on Adaptation and Learning in Multiagent Systems (1996)
Haynes, T., Sen, S.: Cooperation of the Fittest. In: Late Breaking Papers at the Genetic Programming 1996 Conference, July 28-31, Stanford University, Stanford (1996)
Haynes, T., Sen, S.: The Evolution of Multiagent Coordination Strategies. Adaptive Behavior (1997)
Haynes, T., Wainwright, R., Sen, S., Schoenefeld, D.: Strongly Typed Genetic Programming in Evolving Cooperation Strategies. In: Genetic Algorithms: Proceedings of the Sixth International Conference, ICGA 1995 (1995)
Haynes, T., Wainwright, R., Sen, S.: Evolving Cooperation Strategies. In: Proceedings of the First International Conference on Multi–Agent Systems, MIT Press, San Francisco (1995)
Jim, K., Giles, C.L.: Talking Helps: Evolving Communicating Agents for the Predator-Prey Pursuit Problem. Artificial Life 6(3), 237–254 (2000)
Korf, R.: A Simple Solution to Pursuit Games. In: Korf, R. (ed.) Proceedings of the 2nd International Workshop on Distributed Artificial Intelligence, Glen Arbor, Mich. (February 1992)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Natural Selection. MIT Press, Cambridge (1992)
Luke, S., Spector, L.: Teamwork and Coordination with Genetic Programming. In: Genetic Programming 1996: Proceedings of the First Annual Conference, Stanford University, CA, pp. 150–156. MIT Press, USA (1996)
Maes, P., Brooks, R.: Learning to Coordinate Behaviors. In: National Conference on Artificial Intelligence (1990)
Mandl, S., Bimazubute, R., Stoyan, H.: Mobile Intelligent Agents in Erlang. In: Fourth International ICSC Symposium on Engineering of Intelligent Systems, EIS (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mandl, S., Stoyan, H. (2004). Evolution of Agent Coordination in an Asynchronous Version of the Predator-Prey Pursuit Game. In: Lindemann, G., Denzinger, J., Timm, I.J., Unland, R. (eds) Multiagent System Technologies. MATES 2004. Lecture Notes in Computer Science(), vol 3187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30082-3_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-30082-3_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23222-3
Online ISBN: 978-3-540-30082-3
eBook Packages: Springer Book Archive