This repository contains generic platform for solving and benchmarking computational puzzles using different search strategies

Travelling Salesman Problem implementation with Hill Climbing Algorithm

Python Implementation for N-Queen problem using Hill Climbing, Genetic Algorithm, K-Beam Local search and CSP

This repository contains Local Search Algorithms implemented on Magic Square problem.

CIT-316 (Artificial Intelligence Sessional)

codes of my IUT course

Infinit Pacman with JavaScript. Using multiple path-finding algorithms: A*, Greedy Best First Search, and Hill Climbing Search

A multidimensional discrete hill climbing heuristic search algorithm implemented in Python

8-Queens puzzle implementation with Hill Climbing(Random Restart) Algorithm

This repository includes java algorithms and java projects. Code is self explanatory and created using core java concepts in Eclipse Editor. This files are compatible for command line run. Algorithms are demonstrated and explained in comments at end of of main application files.

About It is a Hill Climb Racing Game Controller. The game runs as we move our hand in front of the Primary Camera.

This project was aimed at exploring variations of greedy hill climbing and local search in-order to optimise a real world example.

This repository contains programs using classical Machine Learning algorithms to Artificial Intelligence implemented from scratch and Solving traveling-salesman problem (TSP) using an goal-based AI agent.

In this algorithm, I have written a module which is consist of a couple of main searching algorithm that has been implemented on the 8 puzzle problem as default.

Solving n-queen problem using Python programming language

Solving Shelf Assigning Problem with Hill Climbing, Simulated Annealing and Genetic Algorithms

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..

Hill climbing algorithm is a local search algorithm which continuously moves in the direction of increasing elevation/value to find the peak of the mountain or best solution to the problem. Simulated annealing is a probabilistic technique for approximating the global optimum of a given function.

This consist codes like Artificial Neural Network, CNN, RNN, Activation function, Hill climbing and tower of Hanoi and various others. This will provide you a knowledge of Neural Networks, libraries like tensorflow, numpy, pandas, matplotlib, seaborn, pytorch, sci-kit learn etc