Exact and heuristic methods for solving Boolean games

被引:3
作者
De Clercq, Sofie [1 ]
Bauters, Kim [2 ]
Schockaert, Steven [3 ]
Mihaylov, Mihail [4 ]
Nowe, Ann [4 ]
De Cock, Martine [1 ,5 ]
机构
[1] Univ Ghent, Dept Appl Math, CS & Stat, Ghent, Belgium
[2] Queens Univ, Sch Elect Elect Engn & CS, Belfast, Antrim, North Ireland
[3] Cardiff Univ, Sch Comp Sci & Informat, Cardiff, S Glam, Wales
[4] Vrije Univ Brussel, Artificial Intelligence Lab, Brussels, Belgium
[5] Univ Washington, Ctr Data Sci, Tacoma, WA USA
关键词
Boolean games; Heuristic methods; Answer set programming;
D O I
10.1007/s10458-015-9313-5
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Boolean games are a framework for reasoning about the rational behavior of agents whose goals are formalized using propositional formulas. Compared to normal form games, a well-studied and related game framework, Boolean games allow for an intuitive and more compact representation of the agents' goals. So far, Boolean games have been mainly studied in the literature from the Knowledge Representation perspective, and less attention has been paid on the algorithmic issues underlying the computation of solution concepts. Although some suggestions for solving specific classes of Boolean games have been made in the literature, there is currently no work available on the practical performance. In this paper, we propose the first technique to solve general Boolean games that does not require an exponential translation to normal-form games. Our method is based on disjunctive answer set programming and computes solutions (equilibria) of arbitrary Boolean games. It can be applied to a wide variety of solution concepts, and can naturally deal with extensions of Boolean games such as constraints and costs. We present detailed experimental results in which we compare the proposed method against a number of existing methods for solving specific classes of Boolean games, as well as adaptations of methods that were initially designed for normal-form games. We found that the heuristic methods that do not require all payoff matrix entries performed well for smaller Boolean games, while our ASP based technique is faster when the problem instances have a higher number of agents or action variables.
引用
收藏
页码:66 / 106
页数:41
相关论文
共 28 条
[21]  
Gelfound M., 1988, Logic Programming: Proceedings of the Fifth International Conference and Symposium, P1070
[22]   Pure Nash equilibria: Hard and easy games [J].
Gottlob, G ;
Greco, G ;
Scarcello, F .
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2005, 24 :357-406
[23]  
Gottlob G., 2003, J ARTIF INTELL RES, P215
[24]  
Mihaylov M., 2012, THESIS
[25]   A decentralized approach for convention emergence in multi-agent systems [J].
Mihaylov, Mihail ;
Tuyls, Karl ;
Nowe, Ann .
AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2014, 28 (05) :749-778
[26]  
Papadimitriou C., 1994, Computational complexity
[27]  
Sureka Ashish, 2005, 4 INT JOINT C AUTONO, P1023
[28]   Incentive engineering for Boolean games [J].
Wooldridge, Michael ;
Endriss, Ulle ;
Kraus, Sarit ;
Lang, Jerome .
ARTIFICIAL INTELLIGENCE, 2013, 195 :418-439