Rule-based Genetic Programming

Author

Weise, Thomas ; Zapf, Michael ; Geihs, Kurt

Author_Institution

Univ. of Kassel, Kassel

fYear

2007

fDate

10-12 Dec. 2007

Firstpage

8

Lastpage

15

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.

Keywords

distributed algorithms; genetic algorithms; distributed systems; epistasis; genetic reproduction operations; hard problem; logical operator; rule-based genetic programming; Distributed algorithms; Distributed computing; Genetic algorithms; Genetic programming; Permission; Program processors; Robustness; Space exploration; Testing; Tree graphs; Critical Section; Distributed Algorithms; Epistasis; Genetic Programming; RBGP; Rule-Based Genetic Programming;

fLanguage

English

Publisher

ieee

Conference_Titel

Bio-Inspired Models of Network, Information and Computing Systems, 2007. Bionetics 2007. 2nd

Conference_Location

Budapest

Print_ISBN

978-963-9799-05-9

Electronic_ISBN

978-963-9799-05-9

Type

conf

DOI

10.1109/BIMNICS.2007.4610073

Filename

4610073