Today I released the first public beta of Skynet, which is now at version 0.1.3. Skynet is an implementation of GALib with WPF GUI that solves the Travelling Salesman Problem (TSP) using Genetic Algorithms (GA). It’s completely open source and available under the GNU General Public License.
Downloads
- Skynet 0.1.3.zip 99.4 KB
- Skynet 0.1.3 setup.zip 331.3 KB
- Download GNU tarball (latest version of the source project, straight from SVN)
You can also download the project code directly via SVN from the SourceForge source code repository, at https://csgalib-tsp.svn.sourceforge.net/svnroot/csgalib-tsp. From a command line, you can call the following: svn checkout https://csgalib-tsp.svn.sourceforge.net/svnroot/csgalib-tsp
Application features
- Graphical WPF interface
- Multiple selection algorithms
- Pause, resume and cancellation support
- Control over mutation ratio’s and elitism percentage
- Optional removal of identical twins or individuals
- “Take over the world” button
Background
The idea for creating this application came to me after reading the first part of Bio-Inspired Artificial Intelligence by Dario Floreano and Claudio Mattiussi. I figured I needed to do an implementation of what I’ve read to test myself. I split up the general GA code from the application itself and created GALib, a small C# Library that provides the scaffolding for Genetic Algorithm based functionality. All work was done in my free time.
See this page for more screenshots.
Using the application
Although the application interface should be pretty straight forward to use, I’ve written some documentation, which can be found here. If you have any questions, let me know 🙂
How it works
This section on my wiki explains how Skynet works as an implementation of GALib. If you are not familiar with how genetic algorithms work, you are advised to first have a good look at this Wikipedia article and related pages. This section will introduce you to how GA logic specific to the TSP works in a bottom-up fashion. For more information on the actual evolution, see GALib. I’m also planning to write a Code Project article about this implementation of GALib.
This is a full dependency digram generated in a Visual Studio solution containing both the GALib and Skynet projects.
Points of interest
Since my main motivation for creating this application was exercise, I learned a lot from building it. It’s my first decent C# application, as well as the first time I’ve created one using WPF and the first time I’ve done any GA programming (or AI in general). It also gave me the chance to familiarize myself with some of the new things of .Net 4.0, some profiling tools (see screenshot below), and have some fun with navigation based windows. The biggest challenge in the application itself (so not counting GALib), was definitely creating the crossover algorithm for the Route individual type. At first I simply took half of the connections of one parent, and then the other half from the other parent, but I rewrote this to take all common connections. Although the crossover algorithm works fine now, it’s pretty heavy on the cpu, and limiting the maximum speed of the application severely. If anyone finds a way to speed it up, be sure to let me know 🙂
I’ve been working on this application on an off for a month now, and have implemented everything I’ve planned and more. Although a lot of cool stuff could still be added, I’m quitting active development of both this application and GALib, so I can focus on new projects that allow me to further expand my understanding of AI.