Soft Actor-Critic for Discrete Action Settings

2019-10-16 · Petros Christodoulou

Soft Actor-Critic is a state-of-the-art reinforcement learning algorithm for continuous action settings that is not applicable to discrete action settings. Many important settings involve discrete actions, however, and so here we derive an alternative version of the Soft Actor-Critic algorithm that is applicable to discrete action settings. We then show that, even without any hyperparameter tuning, it is competitive with the tuned model-free state-of-the-art on a selection of games from the Atari suite.

📄 PDF Abstract BibTeX arXiv:1910.07207

Code (13)

p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch 공식 구현 pytorch

BY571/SAC_discrete pytorch

Bigpig4396/PyTorch-Soft-Actor-Critic-SAC pytorch

Epsilon10/MARL pytorch

ToolManChang/DRLseminar_code_challenge

ac-93/soft-actor-critic tf

cindycia/Atari-SAC-Discrete pytorch

keraJLi/rejax jax

ku2482/rljax jax

ku2482/rltorch pytorch

ku2482/sac-discrete.pytorch pytorch

lingweizhu/Pytorch-MunchausenActorCritic pytorch

mindspore-courses/Deep-Reinforcement-Learning-Algorithms-with-MindSpore mindspore

Tasks

Atari Games reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

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Atari Games Q-Learning Reinforcement Learning (RL)

Target Entropy Annealing for Discrete Soft Actor-Critic

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Atari Games Scheduling

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Atari Games continuous-control Continuous Control Reinforcement Learning (RL)

Soft Actor-Critic With Integer Actions

2021-09-17 · Ting-Han Fan, YuBo Wang

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reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Variational Quantum Soft Actor-Critic

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continuous-control Continuous Control reinforcement-learning Reinforcement Learning+1