DD-PPO, TD3, SAC: which is the best?

• habitat-api

  1 752 8.4 Python

  Discontinued A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators. [Moved to: https://github.com/facebookresearch/habitat-lab]

  

Code for https://arxiv.org/abs/1911.00357 found: https://github.com/facebookresearch/habitat-api

• pbt

  1 0 10.0

  Experiments with DeepMind's Population Based Training

Code for https://arxiv.org/abs/1711.09846 found: https://github.com/cipher813/pbt

• InfluxDB

  www.influxdata.com featured

  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.

  

• agents

  11 2,731 8.0 Python

  TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

  

Depending on what task you pick the "best" algo will vary. There are also a bunch of variations and tricks for each of those, some of which have been given new names over time. If you are working on a project I would suggest whichever one has the simplest and most extendable implementation. If you really want to compare all of them you can use libraries that have them all implemented, such as tfagents.

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