mini-AlphaStar
softlearning
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| mini-AlphaStar | softlearning | |
|---|---|---|
| 1 | 4 | |
| 278 | 1,152 | |
| - | 2.3% | |
| 0.0 | 0.0 | |
| over 1 year ago | 5 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mini-AlphaStar
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Better AI opponent
With quick googling I found this, but it seemed like there were no pretrained models and without a tech background this will be pretty much impossible to run.
softlearning
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Problem with Truncated Quantile Critics (TQC) and n-step learning algorithm.
# see https://github.com/rail-berkeley/softlearning/issues/60
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Infinite Horizon problem with SAC and custom environment
Found relevant code at https://github.com/rail-berkeley/softlearning + all code implementations here
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SAC: Enforcing Action Bounds formula derivation
Code for https://arxiv.org/abs/1812.05905 found: https://github.com/rail-berkeley/softlearning
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DDPG not solving MountainCarContinuous
You may read - issue with SAC (https://github.com/rail-berkeley/softlearning/issues/76 ), solution: use large OU noise or use other type of exploration like gSDE
What are some alternatives?
multi_agent_path_planning - Python implementation of a bunch of multi-robot path-planning algorithms.
deep-RL-trading - playing idealized trading games with deep reinforcement learning
DI-drive - Decision Intelligence Platform for Autonomous Driving simulation.
Note - Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, CLIP, ViT, ConvNeXt, SwiftFormer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.
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).
tmrl - Reinforcement Learning for real-time applications - host of the TrackMania Roborace League
sharpy-sc2 - Python framework for rapid development of Starcraft 2 AI bots
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.