Policy Gradient Methods

Twin Delayed Deep Deterministic

Introduced by Fujimoto et al. in Addressing Function Approximation Error in Actor-Critic Methods

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).

Source: Addressing Function Approximation Error in Actor-Critic Methods

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Continuous Control 19 39.58%
OpenAI Gym 6 12.50%
Autonomous Driving 4 8.33%
Decision Making 4 8.33%
Meta-Learning 3 6.25%
Atari Games 2 4.17%
energy management 1 2.08%
Imitation Learning 1 2.08%
Feature Engineering 1 2.08%

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