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TD3

Twin Delayed Deep Deterministic

Reinforcement LearningIntroduced 2000117 papers

Description

TD3 builds on the DDPG algorithm for reinforcement learning, with a couple of modifications aimed at tackling overestimation bias with the value function. In particular, it utilises clipped double Q-learning, delayed update of target and policy networks, and target policy smoothing (which is similar to a SARSA based update; a safer update, as they provide higher value to actions resistant to perturbations).

Papers Using This Method

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning2025-06-06 FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control2025-05-28 LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models2025-05-21 Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control2025-05-13 Energy Efficient RSMA-Based LEO Satellite Communications Assisted by UAV-Mounted BD-Active RIS: A DRL Approach2025-05-07 AlphaGrad: Non-Linear Gradient Normalization Optimizer2025-04-22 Motion Control in Multi-Rotor Aerial Robots Using Deep Reinforcement Learning2025-02-09 TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation2025-02-05 EvoRL: A GPU-accelerated Framework for Evolutionary Reinforcement Learning2025-01-25 Enhancing UAV Path Planning Efficiency Through Accelerated Learning2025-01-17 An Advantage-based Optimization Method for Reinforcement Learning in Large Action Space2024-12-17 Provably Efficient Action-Manipulation Attack Against Continuous Reinforcement Learning2024-11-20 Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers2024-10-31 NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation2024-10-30 Human-Readable Programs as Actors of Reinforcement Learning Agents Using Critic-Moderated Evolution2024-10-29 Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions2024-10-15 Navigation in a simplified Urban Flow through Deep Reinforcement Learning2024-09-26 Simultaneous Training of First- and Second-Order Optimizers in Population-Based Reinforcement Learning2024-08-27 Optimizing TD3 for 7-DOF Robotic Arm Grasping: Overcoming Suboptimality with Exploration-Enhanced Contrastive Learning2024-08-26 Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks2024-07-31