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FLAIRS
2009
13 years 5 months ago
Dynamic Programming Approximations for Partially Observable Stochastic Games
Partially observable stochastic games (POSGs) provide a rich mathematical framework for planning under uncertainty by a group of agents. However, this modeling advantage comes wit...
Akshat Kumar, Shlomo Zilberstein
FSTTCS
2010
Springer
13 years 5 months ago
One-Counter Stochastic Games
We study the computational complexity of basic decision problems for one-counter simple stochastic games (OC-SSGs), under various objectives. OC-SSGs are 2-player turn-based stoch...
Tomás Brázdil, Václav Brozek,...
TON
2008
139views more  TON 2008»
13 years 7 months ago
Stochastic learning solution for distributed discrete power control game in wireless data networks
Distributed power control is an important issue in wireless networks. Recently, noncooperative game theory has been applied to investigate interesting solutions to this problem. Th...
Yiping Xing, Rajarathnam Chandramouli
AAAI
1994
13 years 9 months ago
Acting Optimally in Partially Observable Stochastic Domains
In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
Anthony R. Cassandra, Leslie Pack Kaelbling, Micha...
GECCO
2005
Springer
228views Optimization» more  GECCO 2005»
14 years 1 months ago
Applying metaheuristic techniques to search the space of bidding strategies in combinatorial auctions
Many non-cooperative settings that could potentially be studied using game theory are characterized by having very large strategy spaces and payoffs that are costly to compute. Be...
Ashish Sureka, Peter R. Wurman