Island Model genetic Algorithms and Linearly Separable Problems
Selected Papers from AISB Workshop on Evolutionary Computing
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Automatic Categorization of Human-Coded and Evolved CoreWar Warriors
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
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CoreWar is a computer simulation where two programs written in an assembly language called redcode compete in a virtual memory array. These programs are referred to as warriors. Over more than twenty years of development a number of different battle strategies have emerged, making it possible to identify different warrior types. Systems for automatic warrior creation appeared more recently, evolvers being the dominant kind. This paper describes an attempt to analyze the output of the CCAI evolver, and explores the possibilities for performing automatic categorization by warrior type using representations based on redcode source, as opposed to instruction execution frequency. Analysis was performed using EM clustering, as well as information gain and gain ratio attribute evaluators, and revealed which mainly brute-force types of warriors were being generated. This, along with the observed correlation between clustering and the workings of the evolutionary algorithm justifies our approach and calls for more extensive experiments based on annotated warrior benchmark collections.