TY - GEN
T1 - Finding a nash equilibrium by asynchronous backtracking
AU - Grubshtein, Alon
AU - Meisels, Amnon
PY - 2012/11/7
Y1 - 2012/11/7
N2 - Graphical Games are a succinct representation of multi agent interactions in which each participant interacts with a limited number of other agents. The model resembles Distributed Constraint Optimization Problems (DCOPs) including agents, variables, and values (strategies). However, unlike distributed constraints, local interactions of Graphical Games take the form of small strategic games and the agents are expected to seek a Nash Equilibrium rather than a cooperative minimal cost joint assignment. The present paper models graphical games as a Distributed Constraint Satisfaction Problem with unique k-ary constraints in which each agent is only aware of its part in the constraint. A proof that a satisfying solution to the resulting problem is an ε-Nash equilibrium is provided and an Asynchronous Backtracking algorithm is proposed for solving this distributed problem. The algorithm's completeness is proved and its performance is evaluated.
AB - Graphical Games are a succinct representation of multi agent interactions in which each participant interacts with a limited number of other agents. The model resembles Distributed Constraint Optimization Problems (DCOPs) including agents, variables, and values (strategies). However, unlike distributed constraints, local interactions of Graphical Games take the form of small strategic games and the agents are expected to seek a Nash Equilibrium rather than a cooperative minimal cost joint assignment. The present paper models graphical games as a Distributed Constraint Satisfaction Problem with unique k-ary constraints in which each agent is only aware of its part in the constraint. A proof that a satisfying solution to the resulting problem is an ε-Nash equilibrium is provided and an Asynchronous Backtracking algorithm is proposed for solving this distributed problem. The algorithm's completeness is proved and its performance is evaluated.
UR - https://www.scopus.com/pages/publications/84868280091
U2 - 10.1007/978-3-642-33558-7_66
DO - 10.1007/978-3-642-33558-7_66
M3 - Conference contribution
AN - SCOPUS:84868280091
SN - 9783642335570
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 925
EP - 940
BT - Principles and Practice of Constraint Programming - 18th International Conference, CP 2012, Proceedings
T2 - 18th International Conference on Principles and Practice of Constraint Programming, CP 2012
Y2 - 8 October 2012 through 12 October 2012
ER -