495 search results - page 53 / 99 » Constructing States for Reinforcement Learning |
133
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ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
145
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NIPS
2004
15 years 5 months ago
2004
Schema learning is a way to discover probabilistic, constructivist, predictive action models (schemas) from experience. It includes methods for finding and using hidden state to m...
119
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ICML
2001
IEEE
16 years 4 months ago
2001
IEEE
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
114
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BIOADIT
2004
Springer
15 years 9 months ago
2004
Springer
Abstract. How can artificial or natural agents autonomously gain understanding of its own internal (sensory) state? This is an important question not just for physically embodied ...
123
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IJCAI
2003
15 years 5 months ago
2003
Multi-robot learning faces all of the challenges of robot learning with all of the challenges of multiagent learning. There has been a great deal of recent research on multiagent ...