John Koza's Publications: Year Index::
Koza, John R., Jones, Lee W., Keane,
Martin A., Streeter, Matthew J., and Al-Sakran, Sameer H. 2004. Toward
automated design of industrial-strength analog circuits by means of genetic
O'Reilly, Una-May, Riolo, Rick L., Yu, Gwoing, and
Worzel, William (editors). Genetic
Programming Theory and Practice II.
It has been previously established that genetic programming can be used as an automated invention machine to synthesize 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 synthesize 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 multi-objective fitness measures associated with real-world design problems.
Click here for PDF file of GPTP-2004 paper.
John R., Keane, Martin A., and Streeter, Matthew J. 2004. Routine high-return human-competitive evolvable hardware. In Zebulum, Ricardo S., Gwaltney, David, Hornby,
Gregory, Keymeulen, Didier Lohn, Jason, and Stoica, Adrian (editors). Proceedings of the 2004
NASA/DoD Conference on Evolvable Hardware.
This paper reviews the
use of genetic programming as an automated invention machine for the synthesis
of both the topology and sizing of analog electrical circuits. The paper
focuses on the importance of the developmental representation in this process.
Click here for PDF file of EH-2004 paper.
Koza, John R. 2004. Routine human-competitive machine intelligence by means of genetic
programming. In Proceedings of
Congress On the Future of Engineering Software. Three-page summary of keynote speech in
Genetic programming is a
systematic method for getting computers to automatically solve a problem.
Genetic programming starts from a high-level statement of what needs to be done
and automatically creates a computer program to solve the problem. This summary
Click here for PDF file of COFES-2004 three-page summary of invited talk.
Bijan, Levitt, Raymond E.and Koza, John. R. 2004. Organization design
optimization using genetic programming. In Keijzer, Maarten (editor). Late-Breaking Papers at the 2004 Genetic and
Evolutionary Computation Conference.
This paper describes how we use Genetic Programming
(GP) techniques to help project
managers find near optimal designs for their project organizations. We use GP
as a postprocessor optimizer for the project organization design simulator
Virtual Design Team (VDT). Decision
Click here for a PDF file of this GECCO-2004 late-breaking paper
· The home page of Genetic Programming Inc. at www.genetic-programming.com.
· For information about the field of genetic programming and the field of genetic and evolutionary computation, visit www.genetic-programming.org
· For information about John Koza’s course on genetic algorithms and genetic programming at Stanford University
· Information about the 1992 book Genetic Programming: On the Programming of Computers by Means of Natural Selection, the 1994 book Genetic Programming II: Automatic Discovery of Reusable Programs, the 1999 book Genetic Programming III: Darwinian Invention and Problem Solving, and the 2003 book Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Click here to read chapter 1 of Genetic Programming IV book in PDF format.
· 3,440 published papers on genetic programming (as of November 28, 2003) in a searchable bibliography (with many on-line versions of papers) by over 880 authors maintained by William Langdon’s and Steven M. Gustafson.
· For information on the Genetic Programming and Evolvable Machines journal published by Kluwer Academic Publishers
· For information on the Genetic Programming book series from Kluwer Academic Publishers, see the Call For Book Proposals
information about the annual 2005
Genetic and Evolutionary Computation (GECCO) conference (which includes
the annual GP conference) to be held on June 25–29, 2005 (Saturday – Wednesday)
Last updated on August 14, 2004