A Frequent Pattern Mining Algorithm for Understanding Genetic Algorithms

Authors:
Minh Nghia Le;Yew Soon Ong
Affiliations:
School of Computer Engineering, Nanyang Technological University, Singapore 639798;School of Computer Engineering, Nanyang Technological University, Singapore 639798
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

In this paper, we present a Frequent Schemas Analysis (FSA) approach as an instance of Optinformatics for extracting knowledge on the search dynamics of Binary GA using the optimization data generated during the search. The proposed frequent pattern mining algorithm labeled here as LoFIAin FSA effectively mines for interesting implicit frequent schemas. Subsequently these schemas may be visualized to provide new insights into the workings of the search algorithm. A case study using the Royal Road problem is used to explain the search performance of Genetic Algorithm (GA) based on FSA in action.