Solving even-parity problems using traceless genetic programming
This is an incremental improvement for evolutionary computation in digital circuit design.
The paper tackles the even-parity problem by proposing traceless genetic programming (TGP), a hybrid method that does not explicitly store evolved programs, and reports that TGP outperforms standard GP by several orders of magnitude in numerical experiments.
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 individuals and a technique for representing 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.