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ATAL
2006
Springer
13 years 11 months ago
Learning to commit in repeated games
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
Stéphane Airiau, Sandip Sen
JSAC
2007
189views more  JSAC 2007»
13 years 7 months ago
Non-Cooperative Power Control for Wireless Ad Hoc Networks with Repeated Games
— One of the distinctive features in a wireless ad hoc network is lack of any central controller or single point of authority, in which each node/link then makes its own decision...
Chengnian Long, Qian Zhang, Bo Li, Huilong Yang, X...
SIGECOM
2006
ACM
96views ECommerce» more  SIGECOM 2006»
14 years 1 months ago
Non-cooperative multicast and facility location games
We consider a multicast game with selfish non-cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing de...
Chandra Chekuri, Julia Chuzhoy, Liane Lewin-Eytan,...
AI
2004
Springer
13 years 7 months ago
Efficient learning equilibrium
Efficient Learning Equilibrium (ELE) is a natural solution concept for multi-agent encounters with incomplete information. It requires the learning algorithms themselves to be in ...
Ronen I. Brafman, Moshe Tennenholtz
UAI
2000
13 years 9 months ago
Fast Planning in Stochastic Games
Stochastic games generalize Markov decision processes MDPs to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards de...
Michael J. Kearns, Yishay Mansour, Satinder P. Sin...