Pylearn2
gym
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| Pylearn2 | gym | |
|---|---|---|
| 1 | 96 | |
| 2,752 | 33,873 | |
| 0.0% | 0.8% | |
| 0.0 | 0.0 | |
| over 2 years ago | 20 days ago | |
| Python | Python | |
| BSD 1-Clause License | 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.
Pylearn2
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iNeural : Update (8.12.21)
It is developed by taking inspiration from libraries such as iNeural, FANN, pylearn2, EBLearn, Torch7. Written mostly in C++, iNeural also leverages the power of Python. The biggest reason for its development is that it needs very few dependencies. For this reason, it is expected to be suitable for working in systems with limited system requirements.
gym
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OpenAI Acquires Global Illumination
A co-founder announced they disbanded their robots team a couple years ago: https://venturebeat.com/business/openai-disbands-its-robotic...
That was the same time they depreciated OpenAI Gym: https://github.com/openai/gym
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Shimmy 1.0: Gymnasium & PettingZoo bindings for popular external RL environments
This includes single-agent Gymnasium wrappers for DM Control, DM Lab, Behavior Suite, Arcade Learning Environment, OpenAI Gym V21 & V26. Multi-agent PettingZoo wrappers support DM Control Soccer, OpenSpiel and Melting Pot. For more information, read the release notes here:
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Some confusion about variables and functions in mujoco-py
When I browse fetch_env.py, I have a question about the following code snippet:
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pip install stable-baselines3[extra]
Nvm, this works for me '!pip install setuptools==65.5.0' Source: https://github.com/openai/gym/issues/3176
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[P] Reinforcement learning evolutionary hyperparameter optimization - 10x speed up
how would this interact/compare with https://github.com/openai/gym?
- What has replaced OpenAI Retro Gym?
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Understanding Reinforcement Learning
If you'd like to learn more about reinforcement learning or play with a number of samples in controlled environments, I highly recommend you look at the documentation for OpenAI's Gym library and particularly the basic usage page. OpenAI's Gym provides a standardized environment for performing reinforcement learning on classic Atari games and a few other platforms and should be an educational resource. If you'd like a more detailed example, check out this tutorial on Paperspace's blog.
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Using the cross-entropy method to solve Frozen Lake
Frozen Lake is an OpenAI Gym environment in which an agent is rewarded for traversing a frozen surface from a start position to a goal position without falling through any perilous holes in the ice.
- Is there a publicly available state space model for the Lunar Lander environment?
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How to Create a Behavioral Cloning Bot to Play Online Games?
typically a more relaxed approach is taken via reinforcement learning, but it requires that you can simulate the game via a given gamestate. take a look at e.g. https://www.gymlibrary.dev/
What are some alternatives?
Keras - Deep Learning for humans
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.
SciKit-Learn Laboratory - SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.
carla - Open-source simulator for autonomous driving research.
tensorflow - An Open Source Machine Learning Framework for Everyone
PyBrain
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
scikit-learn - scikit-learn: machine learning in Python
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.