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ATAL
2007
Springer
14 years 1 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
UAI
2008
13 years 8 months ago
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Stéphane Ross, Joelle Pineau
CORR
2012
Springer
196views Education» more  CORR 2012»
12 years 2 months ago
PAC-Bayesian Policy Evaluation for Reinforcement Learning
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
Mahdi Milani Fard, Joelle Pineau, Csaba Szepesv&aa...
AAAI
2010
13 years 8 months ago
Towards Multiagent Meta-level Control
Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to t...
Shanjun Cheng, Anita Raja, Victor R. Lesser