Solving even-parity problems using traceless genetic programming
Solving even-parity problems using traceless genetic programming
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.
7 Figures, 3 Tables
- Babeș-Bolyai University Romania
FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE)
FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE)
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