reinforcement learning

On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference RSS 2012 On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes NeurIPS 2012 Optimistic planning for Markov decision processes AISTATS 2012 Reducing Conservativeness in Safety Guarantees by Learning Disturbances Online: Iterated Guaranteed Safe Online Learning RSS 2012 Regularized Off-Policy TD-Learning NeurIPS 2012 Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds NeurIPS 2012 Sketch-Based Linear Value Function Approximation NeurIPS 2012 Tendon-Driven Variable Impedance Control Using Reinforcement Learning RSS 2012 Timely Object Recognition NeurIPS 2012 Transfer in Reinforcement Learning via Shared Features JMLR 2012 Value Pursuit Iteration NeurIPS 2012 Weighted Likelihood Policy Search with Model Selection NeurIPS 2012 Action-Gap Phenomenon in Reinforcement Learning NeurIPS 2011 Agnostic KWIK learning and efficient approximate reinforcement learning COLT 2011 Analysis and Improvement of Policy Gradient Estimation NeurIPS 2011 A Reinforcement Learning Theory for Homeostatic Regulation NeurIPS 2011 A reinterpretation of the policy oscillation phenomenon in approximate policy iteration NeurIPS 2011 Blending Autonomous Exploration and Apprenticeship Learning NeurIPS 2011 Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery NeurIPS 2011 Convergent Fitted Value Iteration with Linear Function Approximation NeurIPS 2011 Dynamic Policy Programming with Function Approximation AISTATS 2011 Environmental statistics and the trade-off between model-based and TD learning in humans NeurIPS 2011 Exploiting Best-Match Equations for Efficient Reinforcement Learning JMLR 2011 Generalized TD Learning JMLR 2011 Improving Policy Gradient Estimates with Influence Information ACML 2011