princeton-nlp/lwm

We develop world models that can be adapted with natural language. Intergrating these models into artificial agents allows humans to effectively control these agents through verbal communication.

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Emerging

This project helps AI developers build artificial agents that can be controlled and understand their environment using natural language instructions. By providing language descriptions and observing how an agent interacts within a simulated environment, developers can train a 'world model' that predicts outcomes. This model then allows for more effective policy learning to guide the agent's actions.

No commits in the last 6 months.

Use this if you are developing AI agents for environments where natural language commands are crucial for control and understanding.

Not ideal if your AI application doesn't involve complex simulated environments or requires control solely through non-linguistic inputs.

AI-agent-control natural-language-processing simulated-environments robotics-control reinforcement-learning
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 10 / 25

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Stars

25

Forks

3

Language

Python

License

GPL-3.0

Last pushed

Feb 10, 2024

Commits (30d)

0

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