Repo for the Deep Reinforcement Learning Nanodegree program

Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

🎯 A comprehensive gradient-free optimization framework written in Python

📐 Geometrize is a Haxe port of primitive that geometrizes images into geometric primitives

This repository contains implementation of different AI algorithms, based on the 4th edition of amazing AI Book, Artificial Intelligence A Modern Approach

A Java library of Customizable, Hybridizable, Iterative, Parallel, Stochastic, and Self-Adaptive Local Search Algorithms

🔶 C++ library for Geometrize, a tool for geometrizing images into geometric primitives

An algorithm for creating a good timetable for the Faculty of Computing. The algorithm is based on evolutionary strategies, more precisely on the 1+1 evolutionary strategy and Shotgun hill climbing.

Solving and GUI demonstration of traditional N-Queens Problem using Hill Climbing, Simulated Annealing, Local Beam Search, and Genetic Algorithm.

Command-line application to produce generative art based on a target image

A C# Library to aid programming for meta-heuristics

Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.

Solving Knapsack 0/1 problem with various Local Search algorithms like Hill Climbing, Genetic Algorithms, Simulated Annealing, Tabu Search

Enigma cipher tool

Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction

All exercises for the course Elements of AI - Building AI

Reproduce images using geometric primitives

Using Simulated Annealing, Hill Climbing, and Genetic Algorithms to recreate images using shapes 🤖 🧬

Demo using Geometrize Haxe and HaxeFlixel to recreate images with geometric primitives

This is a n-queen problem solver using local search algorithms.