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» Algorithms for Inverse Reinforcement Learning
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CONSTRAINTS
2008
89views more  CONSTRAINTS 2008»
13 years 10 months ago
A Reinforcement Learning Approach to Interval Constraint Propagation
When solving systems of nonlinear equations with interval constraint methods, it has often been observed that many calls to contracting operators do not participate actively to th...
Frédéric Goualard, Christophe Jerman...
ICASSP
2011
IEEE
13 years 1 months ago
Bayesian reinforcement learning for POMDP-based dialogue systems
Spoken dialogue systems are gaining popularity with improvements in speech recognition technologies. Dialogue systems can be modeled effectively using POMDPs, achieving improvemen...
ShaoWei Png, Joelle Pineau
ICANNGA
2007
Springer
105views Algorithms» more  ICANNGA 2007»
14 years 4 months ago
Reinforcement Learning in Fine Time Discretization
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
Pawel Wawrzynski
NECO
2010
103views more  NECO 2010»
13 years 8 months ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
ICML
2005
IEEE
14 years 11 months ago
Relating reinforcement learning performance to classification performance
We prove a quantitative connection between the expected sum of rewards of a policy and binary classification performance on created subproblems. This connection holds without any ...
John Langford, Bianca Zadrozny