TY - GEN
T1 - Co-evolution of strategies for multi-objective games under postponed objective preferences
AU - Eisenstadt, Erella
AU - Moshaiov, Amiram
AU - Avigad, Gideon
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/4
Y1 - 2015/11/4
N2 - The vast majority of studies that are related to game theory are on Single Objective Games (SOG), also known as single payoff games. Multi-Objective Games (MOGs), which are also termed as multi payoff, multi criteria or vector payoff games, have received lesser attention. Yet, in many practical problems, generally each player cope with multiple objectives that might be contradicting. In such problems, a vector of objective functions must be considered. The common approach to deal with MOGs is to assume that the preferences of the players are known. In such a case a utility function is used, which transforms the MOG into a surrogate SOG., This paper deals with non-cooperative MOGs in a non-Traditional way. The zero-sum MOG, which is considered here, involves two players that postponed their objective preferences, allowing them to decide on their preferences after tradeoffs are revealed. To solve such problems we propose a co-evolutionary algorithm based on a worst-case domination relation among sets. The suggested algorithm is tested on a simple differential game (tug-of-war). The obtained results serve to illustrate the approach and demonstrate the applicability of the proposed co-evolutionary algorithm.
AB - The vast majority of studies that are related to game theory are on Single Objective Games (SOG), also known as single payoff games. Multi-Objective Games (MOGs), which are also termed as multi payoff, multi criteria or vector payoff games, have received lesser attention. Yet, in many practical problems, generally each player cope with multiple objectives that might be contradicting. In such problems, a vector of objective functions must be considered. The common approach to deal with MOGs is to assume that the preferences of the players are known. In such a case a utility function is used, which transforms the MOG into a surrogate SOG., This paper deals with non-cooperative MOGs in a non-Traditional way. The zero-sum MOG, which is considered here, involves two players that postponed their objective preferences, allowing them to decide on their preferences after tradeoffs are revealed. To solve such problems we propose a co-evolutionary algorithm based on a worst-case domination relation among sets. The suggested algorithm is tested on a simple differential game (tug-of-war). The obtained results serve to illustrate the approach and demonstrate the applicability of the proposed co-evolutionary algorithm.
UR - http://www.scopus.com/inward/record.url?scp=84964478055&partnerID=8YFLogxK
U2 - 10.1109/CIG.2015.7317915
DO - 10.1109/CIG.2015.7317915
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AN - SCOPUS:84964478055
T3 - 2015 IEEE Conference on Computational Intelligence and Games, CIG 2015 - Proceedings
SP - 461
EP - 468
BT - 2015 IEEE Conference on Computational Intelligence and Games, CIG 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 31 August 2015 through 2 September 2015
ER -