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ATAL
2007
Springer
13 years 11 months ago
Reducing the complexity of multiagent reinforcement learning
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Andriy Burkov, Brahim Chaib-draa
FLAIRS
2009
13 years 3 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
AGI
2011
12 years 9 months ago
Multigame Playing by Means of UCT Enhanced with Automatically Generated Evaluation Functions
General Game Playing (GGP) contest provides a research framework suitable for developing and testing AGI approaches in game domain. In this paper, we propose a new modification of...
Karol Waledzik, Jacek Mandziuk
ATAL
2008
Springer
13 years 7 months ago
Interaction-driven Markov games for decentralized multiagent planning under uncertainty
In this paper we propose interaction-driven Markov games (IDMGs), a new model for multiagent decision making under uncertainty. IDMGs aim at describing multiagent decision problem...
Matthijs T. J. Spaan, Francisco S. Melo
GLOBECOM
2007
IEEE
13 years 11 months ago
Non-Cooperative Power Control for Faded Wireless Ad Hoc Networks
— The problem of non-cooperative power control is studied for wireless ad hoc networks supporting data services. We develop a maximum throughput based non-cooperative power contr...
Xiaolu Zhang, Meixia Tao, Chun Sum Ng