garage
VMAgent
| garage | VMAgent | |
|---|---|---|
| 5 | 1 | |
| 1,813 | 75 | |
| 0.4% | - | |
| 0.0 | 1.4 | |
| almost 1 year ago | about 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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garage
- Are there any follow-up studies of RL^2 algorithms?
- Which python library to pick for RL as a beginner
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Actor-critic reinforce-style gradient with entropy regularization vs soft actor-critic
max: https://github.com/rlworkgroup/garage/blob/62bbc5cec70480e3bf2039cea7f130befecbef10/src/garage/torch/algos/vpg.py#L158 regularized: https://github.com/rlworkgroup/garage/blob/62bbc5cec70480e3bf2039cea7f130befecbef10/src/garage/torch/algos/vpg.py#L343
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Do you have any recommendation on a Reinforcement Learning library for Python?
TF-Agents and Garage look interesting and would be my first stop. Unfortunately I picked OpenAI baselines (not stable baselines) but it isn't supported any more.
- How to do unit testing for reinforcement learning
VMAgent
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Huawei Research Introduces ‘VMAgent’: A Platform for Exploiting Reinforcement Learning (RL) on Virtual Machine (VM) Scheduling Tasks
In a recent study, researchers from Huawei Cloud’s Multi-Agent Artificial Intelligence Lab and Algorithm Innovation Lab suggested VMAgent, a unique VM scheduling simulator based on real data from Huawei Cloud’s actual operation situations. VMAgent seeks to replicate the scheduling of virtual machine requests across many servers (allocating and releasing CPU and memory resources). It creates virtual machine scheduling scenarios using real-world system design, such as fading, recovering, and expanding virtual machines. Only requests can be allocated in the fading situation, whereas the recovering scenario permits both allocating and releasing VM resources.
What are some alternatives?
lightning-hydra-template - PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Metaworld - Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
coo - Schedule Twitter updates with easy
metaworld - Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning [Moved to: https://github.com/Farama-Foundation/Metaworld]
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
nn-template - Generic template to bootstrap your PyTorch project.
maro - Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
rl_lib - Series of deep reinforcement learning algorithms 🤖
oncall - Oncall is a calendar tool designed for scheduling and managing on-call shifts. It can be used as source of dynamic ownership info for paging systems like http://iris.claims.
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.