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» Reinforcement learning with Gaussian processes
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103
Voted
ICML
2003
IEEE
16 years 2 months ago
Q-Decomposition for Reinforcement Learning Agents
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...
Stuart J. Russell, Andrew Zimdars
105
Voted
ECML
2004
Springer
15 years 7 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
CIKM
2008
Springer
15 years 3 months ago
A sparse gaussian processes classification framework for fast tag suggestions
Tagged data is rapidly becoming more available on the World Wide Web. Web sites which populate tagging services offer a good way for Internet users to share their knowledge. An in...
Yang Song, Lu Zhang 0007, C. Lee Giles
103
Voted
ICML
2008
IEEE
16 years 2 months ago
Reinforcement learning in the presence of rare events
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...
Jordan Frank, Shie Mannor, Doina Precup
135
Voted
ICCV
2011
IEEE
14 years 1 months ago
Shape-constrained Gaussian Process Regression for Facial-point-based Head-pose Normalization
Given the facial points extracted from an image of a face in an arbitrary pose, the goal of facial-point-based headpose normalization is to obtain the corresponding facial points ...
Ognjen Rudovic, Maja Pantic