515 search results - page 34 / 103 » Approximating Markov Processes by Averaging |
ICRA
2007
IEEE
15 years 6 months ago
2007
IEEE
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
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ICML
2007
IEEE
16 years 17 days ago
2007
IEEE
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
NIPS
2000
15 years 1 months ago
2000
We propose a method of approximate dynamic programming for Markov decision processes (MDPs) using algebraic decision diagrams (ADDs). We produce near-optimal value functions and p...
ALT
2006
Springer
15 years 8 months ago
2006
Springer
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
111
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NN
2010
Springer
14 years 6 months ago
2010
Springer
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...