2nd International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems

Research Article

Rule-based Genetic Programming

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  • @INPROCEEDINGS{10.4108/ICST.BIONETICS2007.2395,
        author={Thomas Weise and Michael Zapf and Kurt Geihs},
        title={Rule-based Genetic Programming},
        proceedings={2nd International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems},
        proceedings_a={BIONETICS},
        year={2008},
        month={8},
        keywords={Critical Section  Distributed Algorithms  Epistasis  Genetic Programming  RBGP  Rule-Based Genetic Programming},
        doi={10.4108/ICST.BIONETICS2007.2395}
    }
    
  • Thomas Weise
    Michael Zapf
    Kurt Geihs
    Year: 2008
    Rule-based Genetic Programming
    BIONETICS
    ICST
    DOI: 10.4108/ICST.BIONETICS2007.2395
Thomas Weise1,*, Michael Zapf1,*, Kurt Geihs1,*
  • 1: University of Kassel Wilhelmshöher Allee 73 34121 Kassel, Germany
*Contact email: weise@vs.uni-kassel.de, zapf@vs.uni-kassel.de, geihs@vs.uni-kassel.de

Abstract

In this paper we introduce a new approach for Genetic Programming, called rule-based Genetic Programming, or RBGP in short. A program evolved in the RBGP syntax is a list of rules. Each rule consists of two conditions, combined with a logical operator, and an action part. Such rules are independent from each other in terms of position (mostly) and cardinality (always). This reduces the epistasis drastically and hence, the genetic reproduction operations are much more likely to produce good results than in other Genetic Programming methodologies. In order to verify the utility of our idea, we apply RBGP to a hard problem in distributed systems. With it, we are able to obtain emergent algorithms for mutual exclusion at a distributed critical section.