Improving FSM evolution with progressive fitness functions

Authors:
Jason W. Horihan;Yung-Hsiang Lu
Affiliations:
Purdue University;Purdue University
Venue:
Proceedings of the 14th ACM Great Lakes symposium on VLSI
Year:
2004

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Abstract

This paper presents a method to reduce the total number of generations needed to evolve a nite state machine using genetic inferencing. Genetic inferencing is an evolution method that creates designs from their input-output relationship. We reduce the time required to evolve a design by only evolving a small partition of the input-output relationship. We construct the complete design by repeatedly evolving different input-output relationship partitions. Genetically inferring a design with our method can reduce evolution time by more than 80%.