1760 search results - page 73 / 352 » Learning from Partial Observations |
158
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COLT
1998
Springer
15 years 10 months ago
1998
Springer
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
157
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AAAI
2010
15 years 7 months ago
2010
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
142
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UAI
2001
15 years 7 months ago
2001
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
161
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AIMSA
2004
Springer
15 years 10 months ago
2004
Springer
Multi-agent reinforcement learning (MARL) is an emerging area of research. However, it lacks two important elements: a coherent view on MARL, and a well-defined problem objective. ...
155
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CORR
2010
Springer
15 years 6 months ago
2010
Springer
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...