jlin816/dynalang

Code for "Learning to Model the World with Language." ICML 2024 Oral.

38
/ 100
Emerging

This project helps researchers in artificial intelligence develop agents that can understand and interact with simulated environments using language. It takes various forms of language data, such as task descriptions or instructions, and environmental observations (like images or sensor data) as input. The output is an agent capable of predicting future outcomes and performing tasks more effectively within these simulated worlds. It's intended for AI researchers and practitioners working on embodied AI, reinforcement learning, and natural language understanding.

414 stars.

Use this if you are an AI researcher developing agents that need to interpret and utilize language to model their environment and solve tasks within simulated settings.

Not ideal if you are looking for a plug-and-play solution for real-world robotics or a general-purpose natural language processing library.

embodied-ai reinforcement-learning language-understanding simulated-environments agent-development
No License No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 14 / 25

How are scores calculated?

Stars

414

Forks

31

Language

Python

License

Last pushed

Jan 07, 2026

Commits (30d)

0

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