This repository contains implementation of different AI algorithms, based on the 4th edition of amazing AI Book, Artificial Intelligence A Modern Approach
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Updated
May 14, 2024 - Python
This repository contains implementation of different AI algorithms, based on the 4th edition of amazing AI Book, Artificial Intelligence A Modern Approach
Sokobond game developed for the Curricular Unit of Artificial Intelligence. Developed Artificial Intelligence Algorithms to solve 10 different levels, all with different complexities and new game mechanics
This is a Python project that uses Tkinter to develop the front end of the application and Python to implement AI searches. This has a cool graphical interface and visualization to make the project look aesthetic.
AI player for Gobblet Game using MiniMax algorithm with alpha-beta pruning and custom heuristics
A python based chess engine
🧩 Solver for N-Puzzle & N-Queens using Genetic Algorithms, A*, and more in Python
8 puzzle solver, a python program that solves the modified version of Expense 8 puzzle problem using different algorithms,
Python Web Crawler implementing Iterative Deepening Depth Search
A generalized (pq) puzzle solver with Weighted Iterative Deepening A* algorithm, finite state machine pruning routines, and different heuristic methods.
8 Puzzle Solver Using Iterative Deepening Algorithm
Kalaha game written in Python, PyQt and C++
Year 3 SemesterB CS4486 HW1: Implement Iterative A Star(IDA*) Algorithm for path finding, reimplement A* algorithm for finding the path traversing multiple points, and utilized different heuristic functions for the project in the repository forked from udacity/FCND-Motion-Planning
Solving by iterative deepening and hill climbing with random restart
This program uses AI algorithms to clean up the dirt in a 4x5 grid in an efficient way using a vacuum agent.
A python program that implements Artificial Intelligence algorithms such as Iterative Deepening and Hill Climbing Search to find the best solution for the Best Vertex Cover state space
Development of an AI intelligent agent that can play connect 4 using minimax alpha-beta pruning and implementing an IDS
Simple AlphaZero Reinforcement Learning implementation for Go.
Desktop app for visualizing graph search algorithms
A game-playing AI agent is developed for a Competitive Sudoku game using minimax algorithm with alpha-beta pruning and iterative deepening. It is further advanced using heuristics and Monte Carlo Tree Search algorithm.
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