Solving the even-n-parity problems using Best SubTree Genetic Programming

Authors:
Oana Muntean;Laura Diosan;Mihai Oltean
Affiliations:
Babes-Bolyai University, Kogalniceanu 1, Cluj-Napoca, 400084, Romania.;Babes-Bolyai University, Kogalniceanu 1, Cluj-Napoca, 400084, Romania.;Babes-Bolyai University, Kogalniceanu 1, Cluj-Napoca, 400084, Romania.
Venue:
AHS '07 Proceedings of the Second NASA/ESA Conference on Adaptive Hardware and Systems
Year:
2007

Citing 0
Cited 2

An Adaptive GP Strategy for Evolving Digital Circuits

KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
A three-step decomposition method for the evolutionary design of sequential logic circuits

Genetic Programming and Evolvable Machines

Quantified Score

Hi-index	0.00

Visualization

Abstract

Best SubTree Genetic Programming (BSTGP) is a special Genetic Programming (GP) variant whose aim is to offer more possibilities, for selecting the solution, compared to standard GP. In the case of BSTGP the best subtree is chosen for proving the solution. This is different from standard GP where the solution was given by the entire tree. In this paper we apply BSTGP for designing digital circuits for the even-n-parity problem. Numerical results show that BSTGP can improve GP search in terms of success rate and computational effort.