Automated Design of a Previously Patented Aspherical Optical Lens System by Means of Genetic Programming

This chapter describes how genetic programming was used as an invention machine to automatically synthesize a complete design for an aspherical optical lens system (a type of lens system that is especially difficult to design and that offers advantages in terms of cost, weight, size, and performance over traditional spherical systems). The genetically evolved aspherical lens system duplicated the functionality of a recently patented aspherical system. The automatic synthesis was open-ended — that is, the process did not start from a pre-existing good design and did not pre-specify the number of lenses, which lenses (if any) should be spherical or aspherical, the topological arrangement of the lenses, the numerical parameters of the lenses, or the non-numerical parameters of the lenses. The genetically evolved design is an instance of human-competitive results produced by genetic programming in the field of optical design.

[1]  John R. Koza,et al.  Reuse, Parameterized Reuse, and Hierarchical Reuse of Substructures in Evolving Electrical Circuits Using Genetic Programming , 1996, ICES.

[2]  Marc Parizeau,et al.  Lens System Design And Re-engineering With Evolutionary Algorithms , 2002, GECCO.

[3]  John R. Koza,et al.  Genetic programming: a paradigm for genetically breeding populations of computer programs to solve problems , 1990 .

[4]  Peter Nordin,et al.  Genetic programming - An Introduction: On the Automatic Evolution of Computer Programs and Its Applications , 1998 .

[5]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[6]  Scott Brave,et al.  Evolving deterministic finite automata using cellular encoding , 1996 .

[7]  John R. Koza,et al.  Automated Re-invention of a Previously Patented Optical Lens System Using Genetic Programming , 2005, EuroGP.

[8]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[9]  John R. Koza,et al.  Genetic programming 2 - automatic discovery of reusable programs , 1994, Complex Adaptive Systems.

[10]  John R. Koza,et al.  Genetic Programming IV: Routine Human-Competitive Machine Intelligence , 2003 .

[11]  Stewart W. Wilson The Genetic Algorithm and Biological Development , 1987, ICGA.

[12]  Riccardo Poli,et al.  Foundations of Genetic Programming , 1999, Springer Berlin Heidelberg.

[13]  Lee Spector,et al.  Ontogenetic programming , 1996 .

[14]  John R. Koza,et al.  Genetic Programming II , 1992 .

[15]  Fay Sudweeks,et al.  Artificial Intelligence in Design ’96 , 1996, Springer Netherlands.

[16]  Robert F Fischer,et al.  Optical System Design , 2000 .

[17]  John J. Grefenstette,et al.  Genetic algorithms and their applications , 1987 .

[18]  Warren J. Smith Modern lens design : a resource manual , 1992 .

[19]  Przemyslaw Prusinkiewicz,et al.  The Algorithmic Beauty of Plants , 1990, The Virtual Laboratory.

[20]  John R. Koza,et al.  Automated re-invention of six patented optical lens systems using genetic programming , 2005, GECCO '05.

[21]  J. R. Koza,et al.  Darwinian invention and problem solving by means of genetic programming , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[22]  A. Lindenmayer Mathematical models for cellular interactions in development. I. Filaments with one-sided inputs. , 1968, Journal of theoretical biology.

[23]  Hiroaki Kitano,et al.  Designing Neural Networks Using Genetic Algorithms with Graph Generation System , 1990, Complex Syst..

[24]  John R. Koza,et al.  Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming , 1996 .

[25]  John R. Koza,et al.  Discovery of Rewrite Rules in Lindenmayer Systems and State Transition Rules in Cellular Automata via Genetic Programming , 2004 .