67 search results - page 12 / 14 » Learning predictive state representations using non-blind po... |
113
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LAMAS
2005
Springer
15 years 5 months ago
2005
Springer
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
ICML
2007
IEEE
16 years 14 days ago
2007
IEEE
The supremacy of n-gram models in statistical language modelling has recently been challenged by parametric models that use distributed representations to counteract the difficult...
158
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ILP
2007
Springer
15 years 5 months ago
2007
Springer
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
142
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AAAI
2011
13 years 11 months ago
2011
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
127
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ICML
1999
IEEE
16 years 14 days ago
1999
IEEE
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...