PPO-for-Beginners Alternatives
Similar projects and alternatives to PPO-for-Beginners based on common topics and language
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stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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pytorch-learn-reinforcement-learning
A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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PPO-PyTorch
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
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cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
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stable-baselines3-contrib
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
PPO-for-Beginners reviews and mentions
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Why does this PPO implementation calculate the Advantage only once per rollout?
I am looking at this PPO implementation, which follows the pseudocode given in Spinning Up. This implementation has been really easy to follow and I understand almost everything. However, I am lost in line 103, where the author computes the normalized advantage before the rollout -
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ericyangyu/PPO-for-Beginners is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of PPO-for-Beginners is Python.
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