Automated synthesis of a human-competitive solution to the challenge problem of the 2002 international optical design conference by means of genetic programming and a multi-dimensional mutation operation
Author(s) -
Lee W. Jones,
Sameer H. Al-Sakran,
John R. Koza
Publication year - 2006
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-59593-186-4
DOI - 10.1145/1143997.1144143
Subject(s) - computer science , competition (biology) , scratch , genetic algorithm , field (mathematics) , genetic programming , lens (geology) , mathematical optimization , industrial engineering , artificial intelligence , mathematics , programming language , engineering , machine learning , ecology , petroleum engineering , pure mathematics , biology
This paper has two aspects. First, it describes the use of genetic programming to automatically synthesize a solution to the challenge problem posed at an international competition held every four years in the field of optical design. In 2002, the competition at the International Optical Design Conference attracted 42 entries from 39 well-known optical designers, commercial consultants, and patent holders from many of the field's most prominent companies, universities, and research institutions. The 39 human contestants spent an average of 34.1 hours working on their entries. Virtually all entries were considered good solutions to the challenge problem. Genetic programming automatically synthesized a design "from scratch" - that is, without starting from a pre-existing human-created design and without pre-specifying the number of lenses, the physical layout of the lenses, or the numerical or non-numerical parameters of the lenses. The run of genetic programming did not employ any knowledge base of design techniques or principles from the field of optical design and did not entail any human intervention during the run. The genetically evolved optical lens system would have ranked in the middle (21st) if it had been entered into the 2002 competition and is therefore an instance of a "human-competitive" result produced by genetic programming. Second, this paper presents a mutation operation for numerical constants that is especially appropriate for problems in which the to-be-designed structure contains a large number of non-linearly interrelated numerical values and for problems in which the topology of the solution is to be automatically created.
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