Deep RL

Tractable Objectives for Robust Policy Optimization NeurIPS 2012 Transferring Expectations in Model-based Reinforcement Learning NeurIPS 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 Non-Parametric Approach to Dynamic Programming 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 Continuous Rapid Action Value Estimates ACML 2011 Convergent Fitted Value Iteration with Linear Function Approximation NeurIPS 2011 Environmental statistics and the trade-off between model-based and TD learning in humans NeurIPS 2011 Generalized TD Learning JMLR 2011 Infinite-Horizon Model Predictive Control for Periodic Tasks with Contacts RSS 2011 Learning to Agglomerate Superpixel Hierarchies NeurIPS 2011 Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning RSS 2011 Monte Carlo Value Iteration with Macro-Actions NeurIPS 2011 Nonlinear Inverse Reinforcement Learning with Gaussian Processes NeurIPS 2011 Optimal Reinforcement Learning for Gaussian Systems NeurIPS 2011 Policy Gradient Coagent Networks NeurIPS 2011 Reinforcement Learning using Kernel-Based Stochastic Factorization NeurIPS 2011 Robust Approximate Bilinear Programming for Value Function Approximation JMLR 2011