Arcade-Learning-Environment VS bsuite

Compare Arcade-Learning-Environment vs bsuite and see what are their differences.

Arcade-Learning-Environment

The Arcade Learning Environment (ALE) -- a platform for AI research. (by Farama-Foundation)

bsuite

bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent (by google-deepmind)
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Arcade-Learning-Environment bsuite
6 2
2,080 1,470
0.7% 0.8%
5.3 0.0
6 days ago about 1 month ago
C++ Python
GNU General Public License v3.0 only Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

Arcade-Learning-Environment

Posts with mentions or reviews of Arcade-Learning-Environment. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-25.

bsuite

Posts with mentions or reviews of bsuite. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-25.

What are some alternatives?

When comparing Arcade-Learning-Environment and bsuite you can also consider the following projects:

Shimmy - An API conversion tool for popular external reinforcement learning environments

lab - A customisable 3D platform for agent-based AI research

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

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

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