swarna-kpaul/neoplanner

Sequential planner for large text based environments

21
/ 100
Experimental

This tool helps AI researchers and developers design agents that can navigate and solve complex problems in environments described purely through text, even when there are many possible actions and states. It takes a problem description and a large language model API key as input, and outputs a sequence of optimal actions for the agent to take. This is ideal for those building and evaluating AI systems in text-based simulations or interactive fiction games.

No commits in the last 6 months.

Use this if you need an AI agent to efficiently find the best sequence of actions in a text-based environment with a vast number of possibilities.

Not ideal if your environment involves visual or numerical data, or if you are not working with large language models.

AI-agent-design text-based-environments sequential-decision-making large-language-models AI-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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Stars

12

Forks

Language

Python

License

MIT

Last pushed

Dec 13, 2023

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/generative-ai/swarna-kpaul/neoplanner"

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