adaptive
gym
adaptive | gym | |
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11 | 96 | |
1,113 | 33,905 | |
1.4% | 0.5% | |
6.2 | 0.0 | |
6 days ago | 30 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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adaptive
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I made a Python package to do adaptive learning of functions in parallel [P]
Imagine you have a drawing with lots of hills and valleys, and you want to understand the shape of the landscape. Instead of measuring the height at every single point, Adaptive helps you measure the height at the most important points. It focuses on areas where the hills and valleys change a lot, so you can understand the drawing with fewer measurements.
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I made a Python package to do adaptive sampling of functions in parallel [OC]
Yes! Check it out at https://github.com/python-adaptive/adaptive/
Explore and star ⭐️ the repo on github.com/python-adaptive/adaptive, and check out the documentation at adaptive.readthedocs.io.
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Introducing Markdown Code Runner: Automatically execute code blocks in your Markdown files! 🚀
Also, Quatro will require a YAML annotation at the top of the file that will always be visible, e.g., a notebook on GitHub: https://github.com/python-adaptive/adaptive/blob/main/docs/source/tutorial/tutorial.DataSaver.md
- Does Julia have something like pythons adaptive?
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Graph plotting software for nasty function
Getting Python to calculate the equation for you shouldn't be a problem. The problem is that it may be having trouble figuring out which points to sample from. Using a uniformly spaced set of points won't necessarily result in the best looking curve, especially after interpolation. There is the adaptive package which does smart sampling of expensive functions. The idea is you give the function, and the adaptive library will learn the best x values to use and also return f(x).
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?
tensorflow - An Open Source Machine Learning Framework for Everyone
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 - scikit-learn: machine learning in Python
carla - Open-source simulator for autonomous driving research.
Keras - Deep Learning for humans
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
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.