Wave: A Genetic Programming Approach to Divide and Conquer
David Medernach, Jeannie Fitzgerald, R. Muhammad Atif Azad, Conor Ryan
GECCO Companion '15: Companion of the 2015 Annual Conference on Genetic and Evolutionary Computation, Madrid, Spain, 11–15 July 2015, pp. 1435–1436 (poster / extended abstract)
Abstract
This work introduces Wave, a divide and conquer approach to GP whereby a sequence of short, and dependent but potentially heterogeneous GP runs provides a collective solution; the sequence akins wave such that each short GP run is a period of the wave. Heterogeneity across periods results from varying settings of system parameters, such as population size or number of generations, and also by alternating use of the popular GP technique known as linear scaling.
Authors & affiliations
- David Medernach — Biocomputing and Developmental Systems (BDS) Group, Department of Computer Science & Information Systems, University of Limerick, Ireland *
- Jeannie Fitzgerald — Biocomputing and Developmental Systems (BDS) Group, Department of Computer Science & Information Systems, University of Limerick, Ireland
- R. Muhammad Atif Azad — Biocomputing and Developmental Systems (BDS) Group, Department of Computer Science & Information Systems, University of Limerick, Ireland
- Conor Ryan — Biocomputing and Developmental Systems (BDS) Group, Department of Computer Science & Information Systems, University of Limerick, Ireland
* Corresponding author
Keywords
- genetic programming
- divide and conquer
- symbolic regression
- linear scaling
- residual error
- heterogeneous runs
- Wave