Example lecture for Constraint Satisfaction Problems in an interactive jupyter notebook. With python code to solve CSPs, with visualization of Sudoku and NQueens problems.
-
Updated
Dec 7, 2018 - Jupyter Notebook
Example lecture for Constraint Satisfaction Problems in an interactive jupyter notebook. With python code to solve CSPs, with visualization of Sudoku and NQueens problems.
Contains notebook implementations for the AI based assignments using graph based algorithms that are commonly used in solving AI based problems. Algorithms include BFS, DFS, Hill Climbing, Differential Evolution, Genetic, Back Tracking..
Implementation of a Forward-Planning Agent for Udacity's Artificial Intelligence Nanodegree (v3.0). This project is the solution for the notebook from the classroom (topic: Classical Planning).
Add a description, image, and links to the forward-checking topic page so that developers can more easily learn about it.
To associate your repository with the forward-checking topic, visit your repo's landing page and select "manage topics."