DXNN: A Case Study
This chapter presents a case study of a memetic algorithm based TWEANN system that I developed in Erlang, called DXNN. Here we will discuss how DXNN functions, how it is implemented, and the various details and implementation choices I made while building it, and why. We also discuss the various features that it has, the features which we will eventually need to add to the system we’re building together. Our system has a much cleaner and decoupled implementation, and which by the time we’ve reached the last chapter will supersede DXNN in every way.
KeywordsDefend Sonar Plague Drone
- 1.DXNN’s records.hrl is available at: https://github.com/CorticalComputer/DXNN
- 2.Sher GI (2010) Discover & eXplore Neural Network (DXNN) Platform, a Modular TWEANN. Available at: http://arxiv.org/abs/1008.2412
- 3.Gauci J, Stanley KO (2007) Generating Large-Scale Neural Networks Through Discovering Geometric Regularities. Proceedings of the 9th annual conference on Genetic and evolutionary computation GECCO 07, 997.Google Scholar
- 5.Player/Stage/Gazebo: http://playerstage.sourceforge.net/
- 6.Risi S, Stanley KO (2010) Indirectly Encoding Neural Plasticity as a Pattern of Local Rules. Neural Plasticity 6226, 1-11.Google Scholar
- 7.Woolley BG, Stanley KO (2010) Evolving a Single Scalable Controller for an Octopus Arm with a Variable Number of Segments. Parallel Problem Solving from Nature PPSN XI, 270-279.Google Scholar
- 8.DXNN Research Group: www.DXNNResearch.com
- 9.OpenSPARC: http://www.opensparc.net/
- 10.DXNN Neural Network Research Repository: www.DXNNResearch.com/NNRR
- 11.Prdator Vs. Prey Simulation recording: http://www.youtube.com/watch?v=HzsDZt8EO70&feature=related
- 12.Sher GI (2012) Evolving Chart Pattern Sensitive Neural Network Based Forex TradingAgents. Available at: http://arxiv.org/abs/1111.5892.