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Top 23 deep-reinforcement-learning Open-Source Projects
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ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
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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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Scout Monitoring
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AirSim
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
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deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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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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Reinforcement-Learning
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning (by andri27-ts)
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deep-rl-class
This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.
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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).
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awesome-RLHF
A curated list of reinforcement learning with human feedback resources (continually updated)
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rlcard
Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
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Awesome-System-for-Machine-Learning
A curated list of research in machine learning systems (MLSys). Paper notes are also provided.
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rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
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Project mention: How do I change the maximum number of steps for training | /r/MLAgents | 2023-12-07
Project mention: Tesla braces for its first trial involving Autopilot fatality | news.ycombinator.com | 2023-08-28
Project mention: Batendo BOVA11 - Approach usando Reinforcement Learning | /r/farialimabets | 2023-09-11FinRL ---> https://github.com/AI4Finance-Foundation/FinRL
Project mention: Maxtext: A simple, performant and scalable Jax LLM | news.ycombinator.com | 2024-04-23Is t5x an encoder/decoder architecture?
Some more general options.
The Flax ecosystem
https://github.com/google/flax?tab=readme-ov-file
or dm-haiku
https://github.com/google-deepmind/dm-haiku
were some of the best developed communities in the Jax AI field
Perhaps the βtraxβ repo? https://github.com/google/trax
Some HF examples https://github.com/huggingface/transformers/tree/main/exampl...
Sadly it seems much of the work is proprietary these days, but one example could be Grok-1, if you customize the details. https://github.com/xai-org/grok-1/blob/main/run.py
Project mention: Pwnagotchi: Deep Reinforcement Learning for WiFi Hacking | news.ycombinator.com | 2024-01-27
Project mention: [P] PettingZoo 1.24.0 has been released (including Stable-Baselines3 tutorials) | /r/reinforcementlearning | 2023-08-24PettingZoo 1.24.0 is now live! This release includes Python 3.11 support, updated Chess and Hanabi environment versions, and many bugfixes, documentation updates and testing expansions. We are also very excited to announce 3 tutorials using Stable-Baselines3, and a full training script using CleanRL with TensorBoard and WandB.
Project mention: [P] Looking for RL or rules-based No-Limit Hold 'Em Work | /r/MachineLearning | 2023-06-03
Project mention: Open source rules engine for Magic: The Gathering | news.ycombinator.com | 2023-12-14I went looking for MuZero implementations in order to see how, exactly, they interact with the game space. Based on this one, which had the most stars in the muzero topic, it appears that it needs to be able to discern legal next steps from the current game state https://github.com/werner-duvaud/muzero-general/blob/master/...
So, I guess for the cards Forge has implemented one could MuZero it, but I believe it's a bit chicken and egg with a "free text" game like M:TG -- in order to train one would need to know legal steps for any random game state, but in order to have legal steps one would need to be able to read and interpret English rules and card text
While trying to learn the latest in Deep Reinforcement Learning, I was able to take advantage of many excellent resources (see credits [1]), but I couldn't find one that provided the right balance between theory and practice for my personal experience. So I decided to create something myself, and open-source it for the community, in case it might be useful to someone else.
None of that would have been possible without all the resources listed in [1], but I rewrote all algorithms in this series of Python notebooks from scratch, with a with a "pedagogical approach" in mind. It is a hands-on step-by-step tutorial about Deep Reinforcement Learning techniques (up ~2018/2019 SOTA) guiding through theory and coding exercises on the most utilized algorithms (QLearning, DQN, SAC, PPO, etc.)
I shamelessly stole the title from a hero of mine, Andrej Karpathy, and his "Neural Network: Zero To Hero" [2] work. I also meant to work on a series of YouTube videos, but didn't have the time yet. If this posts gets any type of interest, I might go back to it. Thank you.
P.S.: A friend of mine suggested me to post here, so I followed their advice: this is my first post, I hope it properly abides with the rules of the community.
[1] https://github.com/alessiodm/drl-zh/blob/main/00_Intro.ipynb
Project mention: Can't solve MountainCar-v0 with A2C algorithm (stable-baselines3) | /r/reinforcementlearning | 2023-06-27I'm trying to solve MountainCar-v0 enviroment from gymnasium with the A2C algorithm and the agent doesn't find a solution. I checked this so I added import stable_baselines3.common.sb2_compat.rmsprop_tf_like as RMSpropTFLike. Also checked the rl-baselines3-zoo for the hyperparameter tuning. So my code is:
deep-reinforcement-learning related posts
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Deep Reinforcement Learning: Zero to Hero
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AI-generated sad girl with piano performs the text of the MIT License
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Pwnagotchi: Deep Reinforcement Learning for WiFi Hacking
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Making Synthesized Sounds More Acoustic
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FinRL: NEW Deep Learning And Reinforcement Learning - star count:8407.0
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FinRL-Library: started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and [gym](https://gym.openai.com/)
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The Power of Reinforcement Learning: look how this DeepRL Sektor model found a smart, super-cool exploit for Ultimate Mortal Kombat 3 in the video of a submission on DIAMBRA competition platform!
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A note from our sponsor - SaaSHub
www.saashub.com | 1 Jun 2024
Index
What are some of the best open-source deep-reinforcement-learning projects? This list will help you:
Project | Stars | |
---|---|---|
1 | ML-From-Scratch | 23,375 |
2 | ml-agents | 16,462 |
3 | AirSim | 15,962 |
4 | deep-learning-drizzle | 11,850 |
5 | carla | 10,628 |
6 | FinRL | 9,240 |
7 | trax | 7,970 |
8 | pwnagotchi | 7,270 |
9 | introtodeeplearning | 7,016 |
10 | Practical_RL | 5,776 |
11 | cleanrl | 4,633 |
12 | Reinforcement-Learning | 4,091 |
13 | deep-rl-class | 3,667 |
14 | pytorch-a2c-ppo-acktr-gail | 3,491 |
15 | tensorforce | 3,284 |
16 | awesome-RLHF | 2,872 |
17 | minimalRL | 2,725 |
18 | rlcard | 2,740 |
19 | Awesome-System-for-Machine-Learning | 2,490 |
20 | muzero-general | 2,396 |
21 | FinRL-Trading | 1,911 |
22 | drl-zh | 1,896 |
23 | rl-baselines3-zoo | 1,824 |
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