Towards Industrial Strength Automated Design of Analog Electrical Circuits by Means of Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7989

@InCollection{koza:2004:GPTP,

• author = "John R. Koza and Lee W. Jones and Martin A. Keane and Matthew J. Streeter",
• title = "Towards Industrial Strength Automated Design of Analog Electrical Circuits by Means of Genetic Programming",
• booktitle = "Genetic Programming Theory and Practice {II}",
• year = "2004",
• editor = "Una-May O'Reilly and Tina Yu and Rick L. Riolo and Bill Worzel",
• chapter = "8",
• pages = "121--142",
• address = "Ann Arbor",
• month = "13-15 " # may,
• publisher = "Springer",
• note = "pages missing?",
• keywords = "genetic algorithms, genetic programming, Automated design, automated circuit synthesis, analog circuits, amplifier, evolvable hardware, developmental process",
• ISBN = "0-387-23253-2",
• URL = "http://www.genetic-programming.com/gptp2004.pdf",
• DOI = "doi:10.1007/0-387-23254-0_8",
• size = "22 pages",
• abstract = "It has been previously established that genetic programming can be used as an automated invention machine to synthesise designs for complex structures. In particular, genetic programming has automatically synthesized structures that infringe, improve upon, or duplicate the functionality of 21 previously patented inventions (including six 21st-century patented analog electrical circuits) and has also generated two patentable new inventions (controllers). There are seven promising factors suggesting that these previous results can be extended to deliver industrial-strength automated design of analog circuits, but two countervailing factors. This chapter explores the question of whether the seven promising factors can overcome the two countervailing factors by reviewing progress on an ongoing project in which we are employing genetic programming to synthesise an amplifier circuit. The work involves a multiobjective fitness measure consisting of 16 different elements measured by five different test fixtures. The chapter describes five ways of using general domain knowledge applicable to all analog circuits, two ways for employing problem-specific knowledge, four ways of improving on previously published genetic programming techniques, and four ways of grappling with the multiobjective fitness measures associated with real-world design problems.",
• notes = "part of \cite{oreilly:2004:GPTP2}",

}

Genetic Programming entries for John Koza Lee W Jones Martin A Keane Matthew J Streeter

Citations