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» Learning Partially Observable Action Schemas
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ECML
2007
Springer
15 years 5 months ago
Safe Q-Learning on Complete History Spaces
In this article, we present an idea for solving deterministic partially observable markov decision processes (POMDPs) based on a history space containing sequences of past observat...
Stephan Timmer, Martin Riedmiller
95
Voted
ICML
2004
IEEE
16 years 13 days ago
Utile distinction hidden Markov models
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
Daan Wierstra, Marco Wiering
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 6 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
96
Voted
ECCV
2004
Springer
16 years 1 months ago
Decision Theoretic Modeling of Human Facial Displays
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
Jesse Hoey, James J. Little
93
Voted
CORR
2011
Springer
161views Education» more  CORR 2011»
14 years 3 months ago
Doubly Robust Policy Evaluation and Learning
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Miroslav Dudík, John Langford, Lihong Li