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Awesome GitHub RepositoriesContinuous Action Space Tutorials
Educational content teaching how to handle environments where actions are real-valued instead of discrete by extending policy gradient methods.
Distinct from Continuous Control Training: Distinct from Continuous Control Training: focuses on the educational tutorial aspect of continuous action spaces, not the training framework itself.
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Awesome Continuous Action Space Tutorials GitHub Repositories
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- wangshusen/drl
wangshusen/DRL
4,512在 GitHub 上查看DRL is a curated educational resource that teaches deep reinforcement learning through a structured series of lectures and videos. It covers the three main families of reinforcement learning methods: actor-critic architectures, value-based algorithms like Q-learning and DQN, and policy-based techniques that directly optimize an agent's action-selection strategy. The curriculum extends beyond these core topics to include imitation learning, multi-agent training, and methods for handling continuous action spaces. Content is organized as markdown-driven documentation that generates static, navig
Teaches how to handle environments with real-valued actions by extending policy gradient methods.
