Repo for the Deep Reinforcement Learning Nanodegree program
#计算机科学#Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
#算法刷题#🎯 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.
Command-line application to produce generative art based on a target image
Solving and GUI demonstration of traditional N-Queens Problem using Hill Climbing, Simulated Annealing, Local Beam Search, and Genetic Algorithm.
#算法刷题#A C# Library to aid programming for meta-heuristics
Solving Knapsack 0/1 problem with various Local Search algorithms like Hill Climbing, Genetic Algorithms, Simulated Annealing, Tabu Search
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 ...
#计算机科学#All exercises for the course Elements of AI - Building AI
Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction
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
Reproduce images using geometric primitives
This is a n-queen problem solver using local search algorithms.