Ant Colony Optimization For Hackers

Originally proposed in 1992 by Marco Dorigo, ant colony optimization (ACO) is an optimization technique inspired by the path finding behaviour of ants searching for food. ACO is also a subset of swarm intelligence - a problem solving technique using decentralized, collective behaviour, to derive artificial intelligence.

Solving the Traveling Salesman Problem Using Google Maps and Genetic Algorithms

An ideal way to explore the potential of genetic algorithms is by applying them to real world data. Perhaps one of the easiest ways to do this is by using the Google Maps API to implement a solution to the traveling salesman problem.

Introduction to Artificial Neural Networks Part 2 - Learning

In this tutorial we will begin to find out how artificial neural networks can learn, why learning is so useful and what the different types of learning are. We will specifically be looking at training single-layer perceptrons with the perceptron learning rule.

Introduction to Artificial Neural Networks - Part 1

This is the first part of a three part introductory tutorial on artificial neural networks. In this first tutorial we will discover what neural networks are, why they're useful for solving certain types of tasks and finally how they work.

Simulated Annealing for beginners

Simulated Annealing algorithm for beginners. We take a look at what the simulated annealing algorithm is, why it's used and apply it to the traveling salesman problem.

Applying a genetic algorithm to the traveling salesman problem

An introduction to applying a genetic algorithm (GA) to the traveling salesman problem. Beginners Artificial intelligence guide to the travelling salesman problem.

Creating a genetic algorithm for beginners

An introductory tutorial to genetic algorithms (GA) for beginners. Step by step guide of how to create a basic binary genetic algorithm (GA) in Java with example code.