Genetic programming (GP) is an automated invention machine and now delivers routine human-competitive machine intelligence. GP starts from a high-level statement of what needs to be done and uses the Darwinian principle of natural selection to breed a population of improving programs over many generations.
There are now 15 instances where GP has created an entity that either infringes or duplicates the functionality of a patented 20th-century invention, 6 instances where it has done the same with respect to 21st-centry patented inventions, 2 instances where GP has created a patentable new invention, and 13 other human-competitive results produced by GP. These results come from the fields of automated analog circuit synthesis, antenna design, optical system design, controller design, mechanical engineering design, and civil engineering.
Up to now, GP has delivered qualitatively more substantial results in synchrony with the relentless iteration of Moore's Law. We can therefore confidently predict a future acceleration of the automation of the invention process. The inventions produced by GP exhibit the same kind of creativity characteristic of human-produced inventions.
About the speaker:
John R. Koza received his Ph.D. in Computer Science from the University of Michigan in 1972 under the supervision of John Holland. He was co-founder, Chairman, and CEO of Scientific Games Inc. from 1973 through 1987 where he co-invented the rub-off instant lottery ticket used by state lotteries. He is author of four books on genetic programming, including the 2003 book, Genetic Programming IV: Routine Human-Competitive Machine Intelligence. The focus of his research is on automatically solving problems (and, in particular, producing human-competitive results) using a minimum of human-suppplied information. He has taught a course on genetic algorithms and genetic programming at Stanford University since 1988. He is currently a consulting professor in the Biomedical Informatics Program in the Department of Medicine at Stanford University and a consulting professor in the Department of Electrical Engineering at Stanford University.
John R. Koza
Stanford Biomedical Informatics - Dept. of Medicine
Dept. of Electrical Engineering