TY - GEN
T1 - Optimal strategies for multi objective games and their search by evolutionary multi objective optimization
AU - Avigad, G.
AU - Eisenstadt, E.
AU - Cohen, M. Weiss
PY - 2011
Y1 - 2011
N2 - While both games and Multi-Objective Optimization (MOO) have been studied extensively in the literature, Multi-Objective Games (MOGs) have received less research attention. Existing studies deal mainly with mathematical formulations of the optimum. However, a definition and search for the representation of the optimal set, in the multi objective space, has not been attended. More specifically, a Pareto front for MOGs has not been defined or searched for in a concise way. In this paper we define such a front and propose a set-based multi-objective evolutionary algorithm to search for it. The resulting front, which is shown to be a layer rather than a clear-cut front, may support players in making strategic decisions during MOGs. Two examples are used to demonstrate the applicability of the algorithm. The results show that artificial intelligence may help solve complicated MOGs, thus highlighting a new and exciting research direction.
AB - While both games and Multi-Objective Optimization (MOO) have been studied extensively in the literature, Multi-Objective Games (MOGs) have received less research attention. Existing studies deal mainly with mathematical formulations of the optimum. However, a definition and search for the representation of the optimal set, in the multi objective space, has not been attended. More specifically, a Pareto front for MOGs has not been defined or searched for in a concise way. In this paper we define such a front and propose a set-based multi-objective evolutionary algorithm to search for it. The resulting front, which is shown to be a layer rather than a clear-cut front, may support players in making strategic decisions during MOGs. Two examples are used to demonstrate the applicability of the algorithm. The results show that artificial intelligence may help solve complicated MOGs, thus highlighting a new and exciting research direction.
UR - http://www.scopus.com/inward/record.url?scp=80054032593&partnerID=8YFLogxK
U2 - 10.1109/CIG.2011.6032003
DO - 10.1109/CIG.2011.6032003
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AN - SCOPUS:80054032593
SN - 9781457700095
T3 - 2011 IEEE Conference on Computational Intelligence and Games, CIG 2011
SP - 166
EP - 173
BT - 2011 IEEE Conference on Computational Intelligence and Games, CIG 2011
T2 - 2011 7th IEEE International Conference on Computational Intelligence and Games, CIG 2011
Y2 - 31 August 2011 through 3 September 2011
ER -