This project is a Python collection of algorithms and data structures that implement the concepts from the Artificial Intelligence: A Modern Approach textbook. It serves as an educational resource for learning core artificial intelligence concepts through the implementation of classic algorithms for searching, logic, and problem solving.
The repository functions as an automated reasoning toolset for managing knowledge bases, a game theory engine for calculating optimal moves in competitive games, and a search and optimization library. It provides specialized frameworks for deriving logical conclusions through propositional logic and resolution.
The implementation covers several broad capability areas, including pathfinding search, heuristic optimization, constraint satisfaction programming, and the modeling of autonomous agents within structured environments. It includes tools for state-space search graphs, minimax decision trees, and recursive backtracking search.
