Policy Learning

Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms NeurIPS 2008 Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation NeurIPS 2008 Bayesian Policy Learning with Trans-Dimensional MCMC NeurIPS 2007 Fitted Q-iteration in continuous action-space MDPs NeurIPS 2007 Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion NeurIPS 2007 Hierarchical Average Reward Reinforcement Learning JMLR 2007 Incremental Natural Actor-Critic Algorithms NeurIPS 2007 Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning NeurIPS 2007 Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs NeurIPS 2007 Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes JMLR 2007 Random Sampling of States in Dynamic Programming NeurIPS 2007 Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods NeurIPS 2007 Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity NeurIPS 2007 An Application of Reinforcement Learning to Aerobatic Helicopter Flight NeurIPS 2006 Bayesian Policy Gradient Algorithms NeurIPS 2006 Boosting Structured Prediction for Imitation Learning NeurIPS 2006 Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning NeurIPS 2006 Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation JMLR 2006 iLSTD: Eligibility Traces and Convergence Analysis NeurIPS 2006 Learning Nonparametric Models for Probabilistic Imitation NeurIPS 2006 Learning Operational Space Control RSS 2006 Linearly-solvable Markov decision problems NeurIPS 2006 Natural Actor-Critic for Road Traffic Optimisation NeurIPS 2006 Policy Gradient in Continuous Time JMLR 2006 Sample Complexity of Policy Search with Known Dynamics NeurIPS 2006