Arcade-Learning-Environment Alternatives

Similar projects and alternatives to Arcade-Learning-Environment

• gym

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  A toolkit for developing and comparing reinforcement learning algorithms.

  

• stable-baselines3

  46 7,894 8.2 Python Arcade-Learning-Environment VS stable-baselines3

  PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

  

• WorkOS

  workos.com sponsored

  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

• open_spiel

  44 3,999 9.5 C++ Arcade-Learning-Environment VS open_spiel

  OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

  

• PettingZoo

  19 2,370 8.8 Python Arcade-Learning-Environment VS PettingZoo

  An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

  

• dm_control

  7 3,540 7.5 Python Arcade-Learning-Environment VS dm_control

  Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

  

• lab

  4 7,002 0.0 C Arcade-Learning-Environment VS lab

  A customisable 3D platform for agent-based AI research

  

• Shimmy

  1 114 6.2 Python Arcade-Learning-Environment VS Shimmy

  An API conversion tool for popular external reinforcement learning environments

  

• InfluxDB

  www.influxdata.com sponsored

  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.

  

• meltingpot

  4 532 8.9 Python Arcade-Learning-Environment VS meltingpot

  A suite of test scenarios for multi-agent reinforcement learning.

  

• bsuite

  2 1,465 0.0 Python Arcade-Learning-Environment VS bsuite

  bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent