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Reinforcement Learning

2932 directly classified papers

Papers per year

Papers

Sketch-Based Linear Value Function Approximation NIPS 2012
Contextual Bandit Learning with Predictable Rewards AISTATS 2012
On Average Reward Policy Evaluation in Infinite-State Partially Observable Systems AISTATS 2012
On Bayesian Upper Confidence Bounds for Bandit Problems AISTATS 2012
Value Pursuit Iteration NIPS 2012
Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress NIPS 2012
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes NIPS 2012
Trajectory-Based Short-Sighted Probabilistic Planning NIPS 2012
Learned Prioritization for Trading Off Accuracy and Speed NIPS 2012
Learning Partially Observable Models Using Temporally Abstract Decision Trees NIPS 2012
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search NIPS 2012
Symbolic Dynamic Programming for Continuous State and Observation POMDPs NIPS 2012
Regularized Off-Policy TD-Learning NIPS 2012
A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes NIPS 2012
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions NIPS 2012
Timely Object Recognition NIPS 2012
Bayesian Hierarchical Reinforcement Learning NIPS 2012
A Bayesian Approach for Policy Learning from Trajectory Preference Queries NIPS 2012
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization NIPS 2012
A Non-Parametric Approach to Dynamic Programming NIPS 2011
Nonlinear Inverse Reinforcement Learning with Gaussian Processes NIPS 2011
Environmental statistics and the trade-off between model-based and TD learning in humans NIPS 2011
Action-Gap Phenomenon in Reinforcement Learning NIPS 2011
Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning NIPS 2011
MAP Inference for Bayesian Inverse Reinforcement Learning NIPS 2011