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FLAIROx / Kinetix

Reinforcement learning on general 2D physics environments in JAX. ICLR 2025 Oral.

Why this job: says: reinforcement learning; topics: reinforcement-learning

What it does

Kinetix is a framework for reinforcement learning in a 2D rigid-body physics world, written entirely in JAX. Kinetix can represent a huge array of physics-based tasks within a unified framework. We use Kinetix to investigate the training of large, general reinforcement learning agents by procedurally generating millions of tasks for training. You can play with Kinetix in our online editor, or have a look at the JAX physics engine and graphics library we made for Kinetix. Finally, see our docs for more information and more in-depth examples.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 46 days ago
Stars
284
+2 this week
Licence
MIT
Allows business use
Downloads for
None listed
No release files
Latest version
v3.0.2
Released 46 days ago
Built with
Python
100% of the code

Is it looked after?

Contributors
Not stated
Last 90 days
Issues
92% closed
1 still open
Pull requests
27 merged
0 waiting
Releases
7
2 in the last year
  • No contributing guide
  • No security policy
  • No code of conduct

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More: languages, topics and project record

Languages

  • Python 100%

Topics

  • machine-learning
  • physics-engine
  • reinforcement-learning

Project record

  • JobFine-tuning
  • StatusListed
  • Commits44
  • Forks14
  • Watching7
  • Stars in 28 days+8
  • CreatedNov 6, 2024
  • First seen by usNov 7, 2026
  • CheckedNov 8, 2026

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