deep deterministic policy gradient

FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning AAAI 2025 Fuel-Saving Route Planning with Data-Driven and Learning-Based Approaches – A Systematic Solution for Harbor Tugs IJCAI 2024 Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization AISTATS 2024 Off-Policy Average Reward Actor-Critic with Deterministic Policy Search ICML 2023 Reinforcement Learning For Sepsis Treatment: A Continuous Action Space Solution MLHC 2022 Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization UAI 2021 FACMAC: Factored Multi-Agent Centralised Policy Gradients NeurIPS 2021 Leveraging on Deep Reinforcement Learning for Autonomous Safe Decision-Making in Highway On-ramp Merging (Student Abstract) AAAI 2021 Queue-Learning: A Reinforcement Learning Approach for Providing Quality of Service AAAI 2021 Reinforcement Learning Based Multi-Agent Resilient Control: From Deep Neural Networks to an Adaptive Law AAAI 2021 Deterministic Value-Policy Gradients AAAI 2020 Softmax Deep Double Deterministic Policy Gradients NeurIPS 2020 A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems AAAI 2019 Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations ICCV 2019 Maximum Entropy-Regularized Multi-Goal Reinforcement Learning ICML 2019 Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient AAAI 2019 Self-Supervised Mixture-of-Experts by Uncertainty Estimation AAAI 2019 Learning to Explore via Meta-Policy Gradient ICML 2018 Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control ICML 2018 Self-Adaptive Double Bootstrapped DDPG IJCAI 2018 The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously CoRL 2017 Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning CoRL 2017