%0 Book Section %1 koza:2004:GPTP %A Koza, John R. %A Jones, Lee W. %A Keane, Martin A. %A Streeter, Matthew J. %B Genetic Programming Theory and Practice II %C Ann Arbor %D 2004 %E O'Reilly, Una-May %E Yu, Tina %E Riolo, Rick L. %E Worzel, Bill %I Springer %K Automated algorithms, amplifier, analog automated circuit circuits, design, developmental evolvable genetic hardware, process programming, synthesis, %P 120--?? %T Towards Industrial Strength Automated Design of Analog Electrical Circuits by Means of Genetic Programming %U http://www.genetic-programming.com/gptp2004.pdf %X 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. %& 8 %@ 0-387-23253-2

@incollection{koza:2004:GPTP, 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.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Ann Arbor}, author = {Koza, John R. and Jones, Lee W. and Keane, Martin A. and Streeter, Matthew J.}, biburl = {https://www.bibsonomy.org/bibtex/2bce1ed214732dcbb6984fa8aa52fb0dc/brazovayeye}, booktitle = {Genetic Programming Theory and Practice {II}}, chapter = 8, editor = {O'Reilly, Una-May and Yu, Tina and Riolo, Rick L. and Worzel, Bill}, interhash = {1f65d1a8f95ca07268b5af470013a178}, intrahash = {bce1ed214732dcbb6984fa8aa52fb0dc}, isbn = {0-387-23253-2}, keywords = {Automated algorithms, amplifier, analog automated circuit circuits, design, developmental evolvable genetic hardware, process programming, synthesis,}, month = {13-15 May}, note = {pages missing?}, notes = {part of \cite{oreilly:2004:GPTP2}}, pages = {120--??}, publisher = {Springer}, size = {22 pages}, timestamp = {2008-06-19T17:44:16.000+0200}, title = {Towards Industrial Strength Automated Design of Analog Electrical Circuits by Means of Genetic Programming}, url = {http://www.genetic-programming.com/gptp2004.pdf}, year = 2004 }