DocumentCode
3683525
Title
Co-evolution of strategies for multi-objective games under postponed objective preferences
Author
Erella Eisenstadt;Amiram Moshaiov;Gideon Avigad
Author_Institution
School of Mechanical Engineering, Tel Aviv University, Tel Aviv, Israel, and the Department of Mechanical Engineering, ORT Braude College of Engineering, rmiel, Israel
fYear
2015
Firstpage
461
Lastpage
468
Abstract
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.
Keywords
"Games","Sociology","Statistics","Yttrium","Minimization","Sorting","Optimization"
Publisher
ieee
Conference_Titel
Computational Intelligence and Games (CIG), 2015 IEEE Conference on
ISSN
2325-4270
Electronic_ISBN
2325-4289
Type
conf
DOI
10.1109/CIG.2015.7317915
Filename
7317915
Link To Document