Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Computing Factored Value Functions for Policies in Structured MDPs
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Greedy linear value-approximation for factored Markov decision processes
Eighteenth national conference on Artificial intelligence
Dynamic Programming
The Linear Programming Approach to Approximate Dynamic Programming
Operations Research
Solving factored MDPs with continuous and discrete variables
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Samuel meets Amarel: automating value function approximation using global state space analysis
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
An MCMC approach to solving hybrid factored MDPs
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Exploiting structure in policy construction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Planning under continuous time and resource uncertainty: a challenge for AI
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Exploiting Additive Structure in Factored MDPs for Reinforcement Learning
Recent Advances in Reinforcement Learning
Learning Representation and Control in Markov Decision Processes: New Frontiers
Foundations and Trends® in Machine Learning
Solving factored MDPs with hybrid state and action variables
Journal of Artificial Intelligence Research
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We propose two new online methods for estimating the size of a backtracking search tree. The first method is based on a weighted sample of the branches visited by chronological backtracking. The second is a recursive method based on assuming that the ...