Kincho Law

A Category-Theoretic Approach to Neural-Symbolic Task Planning with Bidirectional Search

We introduce a Neural-Symbolic Task Planning framework integrating Large Language Model (LLM) decomposition with category-theoretic verification for resource-aware, temporally consistent planning. Our approach represents states as objects and valid operations as morphisms in a categorical framework,