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ESANN
2006
15 years 1 months ago
Reducing policy degradation in neuro-dynamic programming
We focus on neuro-dynamic programming methods to learn state-action value functions and outline some of the inherent problems to be faced, when performing reinforcement learning in...
Thomas Gabel, Martin Riedmiller
137
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Publication
154views
14 years 2 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
103
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EMNLP
2009
14 years 9 months ago
Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation class...
Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zh...
98
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IJCAI
2007
15 years 1 months ago
Reinforcement Learning of Local Shape in the Game of Go
We explore an application to the game of Go of a reinforcement learning approach based on a linear evaluation function and large numbers of binary features. This strategy has prov...
David Silver, Richard S. Sutton, Martin Mülle...
CORR
2011
Springer
136views Education» more  CORR 2011»
14 years 3 months ago
Reinforcement Learning for Agents with Many Sensors and Actuators Acting in Categorizable Environments
In this paper, we confront the problem of applying reinforcement learning to agents that perceive the environment through many sensors and that can perform parallel actions using ...
Enric Celaya, Josep M. Porta