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Step-by-step instructional resources for implementing specific policy gradient algorithms.
Distinct from Policy Gradient Implementations: Focuses on the tutorial/guide nature of the implementation rather than the architectural implementation itself.
Explore 1 awesome GitHub repository matching artificial intelligence & ml · Learning Guides. Refine with filters or upvote what's useful.
Awesome Learning Guides GitHub Repositories
AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
- morvanzhou/reinforcement-learning-with-tensorflow
MorvanZhou/Reinforcement-learning-with-tensorflow
9,464GitHub पर देखेंThis project is an educational repository of reinforcement learning agents and tutorials implemented using TensorFlow. It provides a practical codebase for both model-free and model-based learning agents, designed to demonstrate how AI agents learn through trial and error. The collection features detailed implementations of various algorithmic approaches, including Deep Q-Networks and Policy Gradient methods. It specifically covers Actor-Critic architectures for continuous and discrete action spaces, alongside Proximal Policy Optimization and Deep Deterministic Policy Gradients. The framewor
Offers guides on optimizing agent behavior by maximizing expected rewards using TensorFlow.
Pythona3cactor-criticasynchronous-advantage-actor-critic
