multi-objective reinforcement learning

A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning NeurIPS 2023 Distributional Pareto-Optimal Multi-Objective Reinforcement Learning NeurIPS 2023 Multi-Objective Reinforcement Learning: Convexity, Stationarity and Pareto Optimality ICLR 2023 On the limitations of Markovian rewards to express multi-objective, risk-sensitive, and modal tasks UAI 2023 PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm ICLR 2023 Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots ICLR 2023 Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL ICLR 2023 Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning NeurIPS 2022 Lexicographic Multi-Objective Reinforcement Learning IJCAI 2022 Pareto Policy Adaptation ICLR 2022 Robust Multi-Objective Reinforcement Learning with Dynamic Preferences ACML 2022 Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning NeurIPS 2021 Multi-Objective Reinforcement Learning for Designing Ethical Environments IJCAI 2021 Provably Efficient Algorithms for Multi-Objective Competitive RL ICML 2021 Reinforcement Learning for Constrained Markov Decision Processes AISTATS 2021 Reinforcement Learning Under Moral Uncertainty ICML 2021 Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards ICML 2020 Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control ICML 2020 A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation NeurIPS 2019 Multi-Objective Reinforcement Learning using Sets of Pareto Dominating Policies JMLR 2014