Paper Info
Title
Cooperation Strategies for Pursuit Games: From a Greedy to an Evolutive Approach
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.
Year
DOI
Venue
2008
10.1007/978-3-540-88636-5_76
MICAI
Keywords
Field
DocType
well-known greedy strategy,evolutive approach,neuroevolution approach,pursuit games,cooperation strategies,new step,greedy algorithm,agent coodination,new way,simple coodination protocol,better coordination,greedy approach,new solution,multi agent system
Computer science,Concurrency,Multi-agent system,Greedy algorithm,Notice,Artificial intelligence,Greedy randomized adaptive search procedure,Neuroevolution,Machine learning
Conference
Volume
ISSN
Citations 
5317
0302-9743
2
PageRank 
References 
Authors
0.41
7
4
Name
Order
Citations
PageRank
juan reverte bernabeu131.22
Francisco Gallego232.58
Rosana Satorre321.76
Faraón Llorens453.78