SKELETAL ALGORITHMS

Michal R. Przybylek

Abstract

This paper introduces a new kind of evolutionary method, called “skeletal algorithm”, and shows its sample application to process mining. The basic idea behind the skeletal algorithm is to express a problem in terms of congruences on a structure, build an initial set of congruences, and improve it by taking limited unions/intersections, until a suitable condition is reached. Skeletal algorithms naturally arise in the context of data/process minig, where the skeleton is the “free” structure on initial data and a congruence corresponds to similarities in data. In such a context, skeletal algorithms come equipped with fitness functions measuring the complexity of a model. We examine two fitness functions for our sample problem — one based on Minimum Description Length Principle, and the other based on Bayesian Interpretation.

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Paper Citation


in Harvard Style

R. Przybylek M. (2011). SKELETAL ALGORITHMS . In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011) ISBN 978-989-8425-83-6, pages 80-89. DOI: 10.5220/0003674700800089


in Bibtex Style

@conference{ecta11,
author={Michal R. Przybylek},
title={SKELETAL ALGORITHMS},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)},
year={2011},
pages={80-89},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003674700800089},
isbn={978-989-8425-83-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)
TI - SKELETAL ALGORITHMS
SN - 978-989-8425-83-6
AU - R. Przybylek M.
PY - 2011
SP - 80
EP - 89
DO - 10.5220/0003674700800089