policy optimization

Clipping Loops for Sample-Efficient Dialogue Policy Optimisation NAACL 2021 Constrained Risk-Averse Markov Decision Processes AAAI 2021 Convex Regularization in Monte-Carlo Tree Search ICML 2021 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee ICML 2021 CTS2: Time Series Smoothing with Constrained Reinforcement Learning ACML 2021 Decoupling Value and Policy for Generalization in Reinforcement Learning ICML 2021 Estimating Disentangled Belief about Hidden State and Hidden Task for Meta-Reinforcement Learning L4DC 2021 Explicable Reward Design for Reinforcement Learning Agents NeurIPS 2021 Fast Stochastic Kalman Gradient Descent for Reinforcement Learning L4DC 2021 Generalizable Imitation Learning from Observation via Inferring Goal Proximity NeurIPS 2021 Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning AISTATS 2021 Independence-aware Advantage Estimation IJCAI 2021 Interaction-Grounded Learning ICML 2021 Iterative Amortized Policy Optimization NeurIPS 2021 Learning from eXtreme Bandit Feedback AAAI 2021 Learning One Representation to Optimize All Rewards NeurIPS 2021 Learning Routines for Effective Off-Policy Reinforcement Learning ICML 2021 Learning While Playing in Mean-Field Games: Convergence and Optimality ICML 2021 Meta-Model-Based Meta-Policy Optimization ACML 2021 Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts IJCAI 2021 Monotonic Robust Policy Optimization with Model Discrepancy ICML 2021 Muesli: Combining Improvements in Policy Optimization ICML 2021 Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers ICML 2021 Nearly Horizon-Free Offline Reinforcement Learning NeurIPS 2021 Near-Optimal Offline Reinforcement Learning via Double Variance Reduction NeurIPS 2021