Title :
Solving even-parity problems using traceless genetic programming
Author_Institution :
Dept. of Comput. Sci., Babes-Bolyai Univ., Cluj-Napoca, Romania
Abstract :
A genetic programming (GP) variant called traceless genetic programming (TGP) is proposed in this paper. TGP is a hybrid method combining a technique for building the individuals and a technique for representing the individuals. The main difference between TGP and other GP techniques is that TGP does not explicitly store the evolved computer programs. Two genetic operators are used in conjunction with TGP: crossover and insertion. TGP is applied for evolving digital circuits for the even-parity problem. Numerical experiments show that TGP outperforms standard GP with several orders of magnitude.
Keywords :
Boolean functions; digital circuits; genetic algorithms; logic programming; parity check codes; search problems; crossover operator; even-parity problems; evolved computer programs; evolving digital circuits; genetic operators; insertion operator; traceless genetic programming; Boolean functions; Circuit analysis; Code standards; Computer science; Digital circuits; Genetic programming; Mathematics;
Conference_Titel :
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN :
0-7803-8515-2
DOI :
10.1109/CEC.2004.1331116