495 search results - page 32 / 99 » Constructing States for Reinforcement Learning |
121
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AIPS
2006
15 years 5 months ago
2006
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
151
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NIPS
1996
15 years 5 months ago
1996
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
192
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AI
1998
Springer
15 years 4 months ago
1998
Springer
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
190
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WAPCV
2007
Springer
15 years 10 months ago
2007
Springer
The innovation of this work is the provision of a system that learns visual encodings of attention patterns and that enables sequential attention for object detection in real world...
141
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ICML
1999
IEEE
16 years 5 months ago
1999
IEEE
Consider the task of exploring the Web in order to find pages of a particular kind or on a particular topic. This task arises in the construction of search engines and Web knowled...