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105
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ATAL
2009
Springer
15 years 7 months ago
2009
Springer
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
93
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ECML
2006
Springer
15 years 4 months ago
2006
Springer
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
96
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ESANN
2008
15 years 2 months ago
2008
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexiti...
110
Voted
CVPR
2007
IEEE
16 years 2 months ago
2007
IEEE
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
99
Voted
ATAL
2003
Springer
15 years 6 months ago
2003
Springer
Much emphasis in multiagent reinforcement learning (MARL) research is placed on ensuring that MARL algorithms (eventually) converge to desirable equilibria. As in standard reinfor...