771 search results - page 128 / 155 » Markov Decision Processes with Arbitrary Reward Processes |
119
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ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...
121
Voted
ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
141
Voted
ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
103
Voted
ICML
2008
IEEE
16 years 2 months ago
2008
IEEE
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
102
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ICML
2006
IEEE
16 years 2 months ago
2006
IEEE
In the model-based policy search approach to reinforcement learning (RL), policies are found using a model (or "simulator") of the Markov decision process. However, for ...