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Recurrent-ppo-truncated-bptt Alternatives
Similar projects and alternatives to recurrent-ppo-truncated-bptt
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ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
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ppo-implementation-details
The source code for the blog post The 37 Implementation Details of Proximal Policy Optimization
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episodic-transformer-memory-ppo
Clean baseline implementation of PPO using an episodic TransformerXL memory
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gym-continuousDoubleAuction
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
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PPO-PyTorch
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
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pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better recurrent-ppo-truncated-bptt alternative or higher similarity.
recurrent-ppo-truncated-bptt discussion
recurrent-ppo-truncated-bptt reviews and mentions
Posts with mentions or reviews of recurrent-ppo-truncated-bptt.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-25.
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What RL library supports custom LSTM and Transformer neural networks to use with algorithms such as PPO?
I provide baseline implementations on TransformerXL + PPO and LSTM/GRU + PPO. These are designed to be slim and easy-to-follow so that you can advance those implementations to the features and toolset that you need.
- How does a recurrent generator work in PPO?
- LSTM encoder in the policy?
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what is the best approach to POMDP environment?
Second, when training a limited view agent in a tabular environment, I expected the rppo agent to perform better than cnn-based ppo. But it didn't. I used this repository that was already implemented and saw slow learning based on this.
- LSTM with SAC not learning well on tasks like Mountain Car and Lunar Lander?
- Recurrent PPO using truncated BPTT
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Stats
Basic recurrent-ppo-truncated-bptt repo stats
6
161
3.2
over 2 years ago
MarcoMeter/recurrent-ppo-truncated-bptt is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of recurrent-ppo-truncated-bptt is Jupyter Notebook.
Popular Comparisons
- recurrent-ppo-truncated-bptt VS ml-agents
- recurrent-ppo-truncated-bptt VS gym-continuousDoubleAuction
- recurrent-ppo-truncated-bptt VS episodic-transformer-memory-ppo
- recurrent-ppo-truncated-bptt VS ppo-implementation-details
- recurrent-ppo-truncated-bptt VS pomdp-baselines
- recurrent-ppo-truncated-bptt VS snakeAI
- recurrent-ppo-truncated-bptt VS PPO-PyTorch
- recurrent-ppo-truncated-bptt VS neroRL
- recurrent-ppo-truncated-bptt VS popgym
- recurrent-ppo-truncated-bptt VS pytorch-a2c-ppo-acktr-gail
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