Abstract
This paper presents a survey of multi-agent systems (MAS) with adversarial teams competing in a dynamic environment. Agents within teams work together against an opposite group of agents in order to fulfill their contrary goals. The article introduces specificity of an environment and indicates fields of cooperation. It emphasizes the role of opponent analysis. Popular planning and learning methods are considered, as well. Next, possible fields of practical application are mentioned. The final part of the paper presents a summary of machine learning methods for specific problem solving and points up future development directions.
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Dzieńkowski, B.J., Markowska-Kaczmar, U. (2012). Agent Cooperation within Adversarial Teams in Dynamic Environment – Key Issues and Development Trends. In: Nguyen, N.T. (eds) Transactions on Computational Collective Intelligence VI. Lecture Notes in Computer Science, vol 7190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29356-6_7
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DOI: https://doi.org/10.1007/978-3-642-29356-6_7
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