508 search results - page 59 / 102 » Learning for stochastic dynamic programming |
121
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AAAI
2010
15 years 4 months ago
2010
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
111
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AAAI
1998
15 years 4 months ago
1998
Probabilistic planning algorithms seek e ective plans for large, stochastic domains. maxplan is a recently developed algorithm that converts a planning problem into an E-Majsat pr...
101
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IDA
2007
Springer
15 years 8 months ago
2007
Springer
We present a new machine learning approach to the inverse parametric sequence alignment problem: given as training examples a set of correct pairwise global alignments, find the p...
117
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IJCV
1998
15 years 2 months ago
1998
The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot repre...
123
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CDC
2010
IEEE
14 years 9 months ago
2010
IEEE
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...