515 search results - page 25 / 103 » Approximating Markov Processes by Averaging |
ICML
2005
IEEE
16 years 16 days ago
2005
IEEE
Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Inter...
ICML
2007
IEEE
16 years 16 days ago
2007
IEEE
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
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ANSS
1996
IEEE
15 years 3 months ago
1996
IEEE
The asymptotic bias and variance are important determinants of the quality of a simulation run. In particular, the asymptotic bias can be used to approximate the bias introduced b...
81
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SARA
2005
Springer
15 years 5 months ago
2005
Springer
Sets of features in Markov decision processes can play a critical role ximately representing value and in abstracting the state space. Selection of features is crucial to the succe...
ICML
2000
IEEE
16 years 16 days ago
2000
IEEE
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...