Cooperation strategies for pursuit games: from a greedy to an evolutive approach

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Title: Cooperation strategies for pursuit games: from a greedy to an evolutive approach
Authors: Reverte Bernabeu, Juan | Gallego-Durán, Francisco J. | Satorre Cuerda, Rosana | Llorens Largo, Faraón
Research Group/s: Informática Industrial e Inteligencia Artificial
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Multi-agent systems | Communication | Coordination | Neuroevolution
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Date Created: 27-Oct-2008
Issue Date: 27-Oct-2008
Publisher: Springer Berlin / Heidelberg
Citation: REVERTE BERNABEU, Juan, et al. "Cooperation strategies for pursuit games: from a greedy to an evolutive approach". En: MICAI 2008: Advances in Artificial Intelligence : 7th Mexican International Conference on Artificial Intelligence, Atizapán de Zaragoza, Mexico, October 27-31, 2008 Proceedings / Gelbukh, Alexander; Morales, Eduardo F. (Eds.). Berlin : Springer, 2008. (Lecture Notes in Computer Science; Vol. 5317). ISBN 978-3-540-88635-8, pp. 806-815
Abstract: Developing coodination among groups of agents is a big challenge in multi-agent systems. An appropriate enviroment to test new solutions is the prey-predator pursuit problem. As it is stated many times in literature, algorithms and conclusions obtained in this environment can be extended and applied to many particular problems. The first solutions for this problem proposed greedy algorithms that seemed to do the job. However, when concurrency is added to the environment it is clear that inter-agent communication and coordination is essential to achieve good results. This paper proposes two new ways to achieve agent coodination. It starts extending a well-known greedy strategy to get the best of a greedy approach. Next, a simple coodination protocol for prey-sight notice is developed. Finally, under the need of better coordination, a Neuroevolution approach is used to improve the solution. With these solutions developed, experiments are carried out and performance measures are compared. Results show that each new step represents an improvement with respect to the previous one. In conclusion, we consider this approach to be a very promising one, with still room for discussion and more improvements.
URI: http://hdl.handle.net/10045/8321
ISBN: 978-3-540-88635-8
ISSN: 0302-9743 (Print) | 1611-3349 (Online)
DOI: 10.1007/978-3-540-88636-5_76
Language: eng
Type: info:eu-repo/semantics/bookPart
Rights: The original publication is available at www.springerlink.com
Peer Review: si
Publisher version: http://dx.doi.org/10.1007/978-3-540-88636-5_76
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