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GPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book Genetic GENETIC-PROGRAMMING.COM-HOME-PAGE Genetic Programming is an Automated Invention Machine. There are now 23 instances where genetic programming has duplicated the functionality of a previously patented invention, infringed a previously issued patent, or created a patentable new invention.GPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book Genetic GENETIC PROGRAMMING: A PARADIGM FOR GENETICALLY 鈥 2 of learning the Boolean multiplexer function is an example of machine learning of a function. In this paper, we show how to discover a composition of elementary Boolean functions for the ITERATIONS, LOOPS, RECURSIONS, AND GENETIC 鈥 Fall 2003 BMI 226 / CS 426 Notes O-3 ITERATION DIFFERENT APPROACHES 鈥 DU ("Do Until") operation (GP-1) 鈥 open-ended number of steps in an iteration 鈥 open-ended number of iterations 鈥 Automatically defined iterations (ADIs) (GP-2). Also called "restricted iteration" 鈥 There is only has a iteration-performing branch (IPB) 鈥 Iteration is over a known, fixed set JOHNKOZA - GENETIC-PROGRAMMING.COM Courses at Stanford University 鈥擩ohn R. Koza. Genetic Algorithms and Genetic Programming Course: BMI 226 / CS 426 / EE392K course on genetic algorithms and genetic programming is co-listed in the Department of Computer Science in the School of Engineering, Department of Electrical Engineering in the School of Engineering, and BioMedical Informatics in the School of Medicine. SURVEY OF GENETIC ALGORITHMS AND GENETIC PROGRAMMING 2. GENETIC PROGRAMMING Genetic programming is an attempt to deal with one of the central questions in computer science (posed by ArthurSamuel
ROUTINE HUMAN-COMPETITIVE MACHINE INTELLIGENCE BY MEANS OF Table 2 Thirty-six human-competitive results produced by genetic programming Claimed instance Basis 1 Creation of a better-than-classical quantum algorithm for the Deutsch-Jozsa 鈥渆arly promise鈥 problem B, F GENETIC-PROGRAMMING.COM-HOME-PAGE How Genetic Programming Works. Genetic programming starts with a primordial ooze of thousands of randomly created computer programs. This population of programs is progre ss ively evolved over a series of generations. The evolutionary search uses the Darwinian principle of natural selection (survival of the fittest) and analogs of various naturally occurring operations, including cro ss over ATTRIBUTES - GENETIC-PROGRAMMING.COM 16 Attributes of a System for Automatic Programming. Genetic programming has 16 attributes of what is sometimes called automatic programming or program synthesis or program induction).. One of the central challenges of computer science is to get a computer to solve a problem without explicitly programming it.GPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book Genetic GENETIC-PROGRAMMING.COM-HOME-PAGE Genetic Programming is an Automated Invention Machine. There are now 23 instances where genetic programming has duplicated the functionality of a previously patented invention, infringed a previously issued patent, or created a patentable new invention.GPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book Genetic GENETIC PROGRAMMING: A PARADIGM FOR GENETICALLY 鈥 2 of learning the Boolean multiplexer function is an example of machine learning of a function. In this paper, we show how to discover a composition of elementary Boolean functions for the ITERATIONS, LOOPS, RECURSIONS, AND GENETIC 鈥 Fall 2003 BMI 226 / CS 426 Notes O-3 ITERATION DIFFERENT APPROACHES 鈥 DU ("Do Until") operation (GP-1) 鈥 open-ended number of steps in an iteration 鈥 open-ended number of iterations 鈥 Automatically defined iterations (ADIs) (GP-2). Also called "restricted iteration" 鈥 There is only has a iteration-performing branch (IPB) 鈥 Iteration is over a known, fixed set JOHNKOZA - GENETIC-PROGRAMMING.COM Courses at Stanford University 鈥擩ohn R. Koza. Genetic Algorithms and Genetic Programming Course: BMI 226 / CS 426 / EE392K course on genetic algorithms and genetic programming is co-listed in the Department of Computer Science in the School of Engineering, Department of Electrical Engineering in the School of Engineering, and BioMedical Informatics in the School of Medicine. SURVEY OF GENETIC ALGORITHMS AND GENETIC PROGRAMMING 2. GENETIC PROGRAMMING Genetic programming is an attempt to deal with one of the central questions in computer science (posed by ArthurSamuel
ROUTINE HUMAN-COMPETITIVE MACHINE INTELLIGENCE BY MEANS OF Table 2 Thirty-six human-competitive results produced by genetic programming Claimed instance Basis 1 Creation of a better-than-classical quantum algorithm for the Deutsch-Jozsa 鈥渆arly promise鈥 problem B, FGPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book Genetic GENETIC-PROGRAMMING.COM-HOME-PAGE Genetic Programming is an Automated Invention Machine. There are now 23 instances where genetic programming has duplicated the functionality of a previously patented invention, infringed a previously issued patent, or created a patentable new invention. INTRODUCTION TO GENETIC PROGRAMMING TUTORIAL GECCO 鈥 3 MAIN POINTS 鈥 Genetic programming now routinely delivers high-return human-competitive machine intelligence. 鈥 Genetic programming is an automated invention machine. 鈥 Genetic programming can automatically create a general solution to a problem in the formof a
JOHNKOZA - GENETIC-PROGRAMMING.COM Courses at Stanford University 鈥擩ohn R. Koza. Genetic Algorithms and Genetic Programming Course: BMI 226 / CS 426 / EE392K course on genetic algorithms and genetic programming is co-listed in the Department of Computer Science in the School of Engineering, Department of Electrical Engineering in the School of Engineering, and BioMedical Informatics in the School of Medicine. HUMAN-COMPETITIVE RESULTS PRODUCED BY GENETIC PROGRAMMING Table 1 Human-competitive results produced by genetic programming Year Authors Title Human-Competitive Prize Award Patent References 1 1994 John R. Koza Creation of algorithm for the transmembrane segment identi铿乧ation problem for proteins USE OF GENETIC PROGRAMMING TO FIND AN IMPULSE 鈥 USE OF GENETIC PROGRAMMING TO FIND AN IMPULSE RESPONSE FUNCTION IN SYMBOLIC FORM( *) John R. Koza (1), Martin A. Keane (2) and James P. Rice (3) Abstract: The recently developed genetic programming paradigmprovides a way to
A PARALLEL IMPLEMENTATION OF GENETIC PROGRAMMING THAT solve a problem using various migration rates. Section 6 describes the successful implementation of a variant of our parallel system where a PowerPC is joined with a transputer at each node of the VERSION 3 鈥 JUNE 25, 1996 FOR HANDBOOK OF EVOLUTIONARY 1 Version 3 鈥 June 25, 1996 for Handbook of Evolutionary Computation. Future Work and Practical Applications of Genetic Programming John R. Koza Computer Science Department StanfordUniversity
GENETIC EVOLUTION AND CO-EVOLUTION OF GAME STRATEGIES 1 Presented July 15, 1992 to the International Conference on Game Theory and Its Applications held at Stony Brook, New York. GENETIC EVOLUTION AND CO-EVOLUTION OF GAME STRATEGIES A GENETIC APPROACH TO FINDING A CONTROLLER TO BACK UP A Submitted September 10, 1991 to 1992 American Control Conference (ACC) to be held in Chicago on June 24-26, 1992 A Genetic Approach toFinding
GENETIC-PROGRAMMING.COM-HOME-PAGE How Genetic Programming Works. Genetic programming starts with a primordial ooze of thousands of randomly created computer programs. This population of programs is progre ss ively evolved over a series of generations. The evolutionary search uses the Darwinian principle of natural selection (survival of the fittest) and analogs of various naturally occurring operations, including cro ss over GENETIC-PROGRAMMING.COM-HOME-PAGE Genetic Programming is an Automated Invention Machine. There are now 23 instances where genetic programming has duplicated the functionality of a previously patented invention, infringed a previously issued patent, or created a patentable new invention.GPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book Genetic ITERATIONS, LOOPS, RECURSIONS, AND GENETIC 鈥 Fall 2003 BMI 226 / CS 426 Notes O-3 ITERATION DIFFERENT APPROACHES 鈥 DU ("Do Until") operation (GP-1) 鈥 open-ended number of steps in an iteration 鈥 open-ended number of iterations 鈥 Automatically defined iterations (ADIs) (GP-2). Also called "restricted iteration" 鈥 There is only has a iteration-performing branch (IPB) 鈥 Iteration is over a known, fixed set USE OF GENETIC PROGRAMMING TO FIND AN IMPULSE 鈥 USE OF GENETIC PROGRAMMING TO FIND AN IMPULSE RESPONSE FUNCTION IN SYMBOLIC FORM( *) John R. Koza (1), Martin A. Keane (2) and James P. Rice (3) Abstract: The recently developed genetic programming paradigmprovides a way to
CONCEPT FORMATION AND DECISION TREE INDUCTION USING 鈥 4 task. In particular, the set of terminals is the set of class names. The set of functions is the set of attribute-based tests. Note that this set of attribute-based GENETIC EVOLUTION AND CO-EVOLUTION OF COMPUTER 鈥 Revised November 29, 1990 for Proceedings of Second Conference on Artificial Life (AL-2) GENETIC EVOLUTION AND CO-EVOLUTION OF COMPUTER PROGRAMS John R. Koza Computer Science Department Margaret Jacks Hall AUTOMATED DESIGN OF BOTH THE TOPOLOGY AND SIZING OF 鈥 AUTOMATED TOPOLOGY AND SIZING OF ANALOG CIRCUITS SPICE (an acronym for Simulation Program with Integrated Circuit Emphasis) is a massive family of programs written over several decades at the University ofCalifornia
AUTOMATICALLY DEFINED FUNCTIONS (ADFS Fall 2003 BMI 226 / CS 426 Notes F-10 AUTOMATICALLY DEFINED FUNCTIONS (ADFS, SUBROUTINES) 鈥 Genetic operation of reproduction is the same as before 鈥 Mutation operation starts (as before) by picking a mutation point from either RPB or an ADF and deleting the subtreerooted at
VERSION 3 鈥 JUNE 25, 1996 FOR HANDBOOK OF EVOLUTIONARY 1 Version 3 鈥 June 25, 1996 for Handbook of Evolutionary Computation. Future Work and Practical Applications of Genetic Programming John R. Koza Computer Science Department StanfordUniversity
GENETIC-PROGRAMMING.COM-HOME-PAGE How Genetic Programming Works. Genetic programming starts with a primordial ooze of thousands of randomly created computer programs. This population of programs is progre ss ively evolved over a series of generations. The evolutionary search uses the Darwinian principle of natural selection (survival of the fittest) and analogs of various naturally occurring operations, including cro ss over GENETIC-PROGRAMMING.COM-HOME-PAGE Genetic Programming is an Automated Invention Machine. There are now 23 instances where genetic programming has duplicated the functionality of a previously patented invention, infringed a previously issued patent, or created a patentable new invention.GPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book Genetic ITERATIONS, LOOPS, RECURSIONS, AND GENETIC 鈥 Fall 2003 BMI 226 / CS 426 Notes O-3 ITERATION DIFFERENT APPROACHES 鈥 DU ("Do Until") operation (GP-1) 鈥 open-ended number of steps in an iteration 鈥 open-ended number of iterations 鈥 Automatically defined iterations (ADIs) (GP-2). Also called "restricted iteration" 鈥 There is only has a iteration-performing branch (IPB) 鈥 Iteration is over a known, fixed set USE OF GENETIC PROGRAMMING TO FIND AN IMPULSE 鈥 USE OF GENETIC PROGRAMMING TO FIND AN IMPULSE RESPONSE FUNCTION IN SYMBOLIC FORM( *) John R. Koza (1), Martin A. Keane (2) and James P. Rice (3) Abstract: The recently developed genetic programming paradigmprovides a way to
CONCEPT FORMATION AND DECISION TREE INDUCTION USING 鈥 4 task. In particular, the set of terminals is the set of class names. The set of functions is the set of attribute-based tests. Note that this set of attribute-based GENETIC EVOLUTION AND CO-EVOLUTION OF COMPUTER 鈥 Revised November 29, 1990 for Proceedings of Second Conference on Artificial Life (AL-2) GENETIC EVOLUTION AND CO-EVOLUTION OF COMPUTER PROGRAMS John R. Koza Computer Science Department Margaret Jacks Hall AUTOMATED DESIGN OF BOTH THE TOPOLOGY AND SIZING OF 鈥 AUTOMATED TOPOLOGY AND SIZING OF ANALOG CIRCUITS SPICE (an acronym for Simulation Program with Integrated Circuit Emphasis) is a massive family of programs written over several decades at the University ofCalifornia
AUTOMATICALLY DEFINED FUNCTIONS (ADFS Fall 2003 BMI 226 / CS 426 Notes F-10 AUTOMATICALLY DEFINED FUNCTIONS (ADFS, SUBROUTINES) 鈥 Genetic operation of reproduction is the same as before 鈥 Mutation operation starts (as before) by picking a mutation point from either RPB or an ADF and deleting the subtreerooted at
VERSION 3 鈥 JUNE 25, 1996 FOR HANDBOOK OF EVOLUTIONARY 1 Version 3 鈥 June 25, 1996 for Handbook of Evolutionary Computation. Future Work and Practical Applications of Genetic Programming John R. Koza Computer Science Department StanfordUniversity
GPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book GeneticGPANIMATEDTUTORIAL
稵he home page of Genetic Programming Inc. at www.genetic-programming.com. 路 For information about the field of genetic programming in general, visit www.genetic-programming.org 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at Stanford University 路 Information about the 1992 book GeneticProgramming
PUBLICATIONS_JOHN_KOZA_1994 1994. Koza, John R. 1994a. Genetic Programming II: Automatic Discovery of Reusable Programs. Cambridge, MA: The MIT Press.. It is often argued that the process of solving complex problems can be automated by first decomposing the problem into subproblems, then solving the presumably simpler subproblems, and then assembling the solutions to the subproblems into an overall solution to the TABLE OF CONTENTS 1. INTRODUCTION 1 2 GENE DUPLICATION AND 2 2. Gene Duplication and Deletion in Nature In nature, deoxyribonucleic acid (DNA) is a long thread-like biological molecule that has the ability to carry hereditary information. PUBLICATIONS_JOHN_KOZA_1972_TO_1993 1972. Koza, John R. 1972. On Inducing a Non-Trivial, Parsimonious, Hierarchical Grammar for a Given Sample of Sentences. Ph.D. dissertation, Department of Computer Science, University of Michigan.Also available as Technical Report 142 of the Logic of Computers Group, Department of Computer and Communications Sciences, University of Michigan. The thesis presents an algorithm which, for agiven
FORREST H BENNETT III Forrest H Bennett III. 路 The home page of Genetic Programming Inc. at www.genetic-programming.com . 路 For information about the field of genetic programming in general, visit www.genetic-programming.org. 路 The home page of John R. Koza at Genetic Programming Inc. (including online versions of most papers) and the home page of John R. Koza at GENETIC PROGRAMMING: WILL BILL GATES BECOME BILLY APPLESEED? Genetic Programming. Will Bill Gates become Billy Appleseed? by Darin Molnar I've never considered myself to be a conspiracy theorist, or even a suspicious person, but events sometimes occur in ways that make even the staunchest skeptic start wondering what the heck is going on. GENETIC EVOLUTION AND CO-EVOLUTION OF COMPUTER 鈥 Revised November 29, 1990 for Proceedings of Second Conference on Artificial Life (AL-2) GENETIC EVOLUTION AND CO-EVOLUTION OF COMPUTER PROGRAMS John R. Koza Computer Science Department Margaret Jacks Hall GENETIC EVOLUTION AND CO-EVOLUTION OF GAME STRATEGIES 1 Presented July 15, 1992 to the International Conference on Game Theory and Its Applications held at Stony Brook, New York. GENETIC EVOLUTION AND CO-EVOLUTION OF GAME STRATEGIES PERFORMANCE IMPROVEMENT OF MACHINE LEARNING VIA AUTOMATIC pixels but is, instead, parameterized, and to then reuse the generalized feature detector to recognize occurrences of the feature in different 3 by 3 pixel regions within the array. IMMEDIATE OPENING (UUPDATED AUGUST JULY 8, 2007)for
scientific research programmer at Genetic Programming Inc. -------------------------_WELCOME TO_
WWW.GENETIC-PROGRAMMING.COM _(THE HOME PAGE OF GENETIC PROGRAMMING INC., A PRIVATELY FUNDED RESEARCH GROUP THAT DOES RESEARCH IN APPLYING GENETIC PROGRAMMING)_ ------------------------- Last updated July 8, 2007 ------------------------- WHAT IS GENETIC PROGRAMMING (GP)? HOW GENETIC PROGRAMMING WORKS SOURCES OF INFORMATION ABOUT THE FIELD OF GENETIC PROGRAMMING (GP), GENETIC ALGORITHMS (GA), AND THE FIELD OF GENETIC AND EVOLUTIONARYCOMPUTATION (GEC)
CONFERENCES ABOUT GENETIC PROGRAMMING (GP) AND GENETIC AND EVOLUTIONARY COMPUTATION (GEC) APPLICATION AREAS FOR GENETIC PROGRAMMING NEWS ABOUT GENETIC PROGRAMMING PARALLELIZATION OF GENETIC PROGRAMMING JOHN KOZA鈥橲 PUBLICATIONS ON GENETIC PROGRAMMINGWEBSMASTER
OTHER LINKS
------------------------- WHAT IS GENETIC PROGRAMMING (GP)? Genetic programming (GP) is an automated method for creating a working computer program from a high-level problem statement of a problem. Genetic programming starts from a high-level statement of 鈥渨hat needs to be done鈥 and automatically creates a computer program tosolve the problem.
There are now 36 INSTANCES WHERE GENETIC PROGRAMMING HAS AUTOMATICALLY PRODUCED A RESULT THAT IS COMPETITIVE WITH HUMAN PERFORMANCE,
including聽 15 instances where genetic programming has created an entity that either infringes or duplicates the functionality of a previously patented 20th-century invention, 6 instances where genetic programming has done the same with respect to a 21st-centry invention, and 2 instances where genetic programming has created a patentable newinvention.
Given these results, we say that 鈥淕enetic programming now routinely delivers high-return human-competitive machine intelligence.鈥 Click here for our definitions of 鈥淗UMAN-COMPETITIVE,鈥THE 鈥淎I
RATIO鈥 (鈥淎RTIFICIAL-TO-INTELLIGENCE鈥 RATIO) AND鈥淗IGH-RETURN,鈥
鈥淩OUTINE,鈥
and 鈥淢ACHINE
INTELLIGENCE.鈥
This
statement is the most important point of the 2003 book _GENETIC PROGRAMMING IV: ROUTINE HUMAN-COMPETITIVE MACHINE INTELLIGENCE_. Click here to
read CHAPTER 1 OF _GENETIC PROGRAMMING IV_ IN PDF FORMAT.Click here for
2004 AWARDS FOR HUMAN-COMPETITIVE RESULTS(based on
presentations at the GECCO-2004 conference in Seattle on June 27,2004).
The fact that genetic programming can evolve entities that are competitive with human-produced results suggests that GENETIC PROGRAMMING CAN BE USED AS AN AUTOMATED INVENTION MACHINEto create
new and useful patentable inventions. In acting as an invention machine, evolutionary methods, such as genetic programming, have the advantage of not being encumbered by preconceptions that limit human problem-solving to well-troden paths. Genetic programming has delivered a PROGRESSION OF QUALITATIVELY MORE SUBSTANTIAL RESULTSin synchrony
with five approximately order-of-magnitude increases in the expenditure of computer time (over the 15-year period from 1987 to2002).
Genetic programming has 16 important attributes that one would reasonably expect of a system for AUTOMATIC PROGRAMMING(sometimes also
called _program synthesis_ or _program induction_). Genetic programming has SEVEN IMPORTANT DIFFERENCESfrom conventional
approaches to artificial intelligence (AI) and machine learning (ML). For additional information, click here for POWERPOINT (PPT) PRESENTATION ON GENETIC PROGRAMMING(about
5 Megabytes) similar to that presented at the 2003 Accelerating Change Conference on September 13, 2003 and similar to the overview lecture given on September 24, 2003 in John Koza鈥檚 course at Stanford University on genetic algorithms (GA) and genetic programming (GP). ------------------------- HOW GENETIC PROGRAMMING WORKS Genetic programming starts with a primordial ooze of thousands of randomly created computer programs. This population of programs is progressively evolved over a series of generations. The evolutionary search uses the Darwinian principle of natural selection (survival of the fittest) and analogs of various naturally occurring operations, including crossover (sexual recombination), mutation, gene duplication, gene deletion. Genetic programming sometimes also employs developmental processes by which an embryo grows into fully developed organism. Old Chinese saying says 鈥渁nimated gif is worth one mega-word,鈥 so CLICK HERE FOR SHORT TUTORIAL OF 鈥淲HAT IS GP?鈥 INCLUDING ABOUT TWO DOZEN ANIMATED GIFS. This
short tutorial contains a discussion of the PREPARATORY STEPSof a run of
genetic programming, the executional steps (that is, the FLOWCHART OFGENETIC PROGRAMMING
), an
ILLUSTRATIVE SIMPLE RUN OF GENETIC PROGRAMMINGfor a
problem of symbolic regression of a quadratic polynomial, a discussion of DEVELOPMENTAL GENETIC PROGRAMMINGfor the
automatic synthesis of both the topology and sizing of analog electrical circuits (potentially also including placement and routing), and the use of a TURTLEto draw complex
structures (such as antenna). In addition, genetic programming can automatically create, in a single run, a general (parameterized) solution to a problem in the form of a graphical structure whose nodes or edges represent components and where the parameter values of the components are specified by mathematical expressions containing free variables. That is, genetic programming can automatically create a _general solution_ to a problem in the form of a PARAMETERIZEDTOPOLOGY .
------------------------- SOURCES OF INFORMATION ABOUT THE FIELD OF GENETIC PROGRAMMING (GP), GENETIC ALGORITHMS (GA), AND THE FIELD OF GENETIC AND EVOLUTIONARYCOMPUTATION (GEC)
The technique of genetic programming (GP) is one of the techniques of the field of genetic and evolutionary computation (GEC) which, in turn, includes techniques such as genetic algorithms (GA), evolution strategies (ES), evolutionary programming (EP), grammatical evolution (GE), and machine code (linear genome) genetic programming. * 16 AUTHORED BOOKS, 4 VIDEOS, AND 4 EDITED BOOKS ON GENETICPROGRAMMING (GP) ,
including 6 BOOKS
in the Genetic Programming Book series from Kluwer Academic Publishers (as part of the bigger list of 73 AUTHORED BOOKS, 32 EDITED BOOKS, AND 4 VIDEOS ON GENETIC AND EVOLUTIONARY COMPUTATION).
* 17 CONFERENCE PROCEEDINGS BOOKS ON GENETIC PROGRAMMING (GP), including the
3 annual GP conferences, 5 annual GECCO conferences (that now include the annual GP conference), 6 annual Euro-GP conferences, the 2003 Genetic Programming Theory and Practice workshop (GPTA), the 1995 AAAI Symposium on Genetic Programming, and the 1995 Workshop on Genetic Programming (as part of a bigger list of 99 CONFERENCE PROCEEDINGS BOOKS ON EVOLUTIONARY COMPUTATION). * 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鈥檚 and Steven M. Gustafson * OVER 4,000 PUBLISHED PAPERS ON EVOLUTIONARY COMPUTATIONin a
searchable bibliography maintained by Karsten Weicker and Nicole Weicker containing entries on genetic and evolutionary computation and related areas (e.g. artificial life). * ABOUT TWO DOZEN CONFERENCES WITH PUBLISHED PROCEEDINGSthat are held
regularly in the field of genetic programming and genetic and evolutionary computation (GEC) * 2004 AWARDS FOR HUMAN-COMPETITIVE RESULTS(based on
presentations at the GECCO-2004 conference in Seattle on June 27,2004).
* E-MAIL MAILING LIST ON GENETIC PROGRAMMING, the EC-Digest
(formerly the GA-Digest), and other mailing lists. * _GENETIC PROGRAMMING AND EVOLVABLE MACHINES _journal (published by Kluwer Academic Publishers and edited by Wolfgang Banzhaf) (started January 2000). This journal is available as part of membership in the INTERNATIONAL SOCIETY FOR GENETIC AND EVOLUTIONARY COMPUTATION (ISGEC) * _EVOLUTIONARY COMPUTATION JOURNAL_(published
by THE MIT PRESS and edited by Marc Schoenauer). This journal is available as part of membership in INTERNATIONAL SOCIETY FOR GENETIC AND EVOLUTIONARY COMPUTATION (ISGEC) * _IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION JOURNAL _(published by IEEE Neural Network Society and edited by Xin Yao)* SOFTWARE for
genetic programming, genetic algorithms, and other evolutionary computation techniques, including the "LITTLE LISP" COMPUTER CODEfor Genetic
Programming as Contained in 1992 book _Genetic Programming_ (Koza1992)
* 37 COMPLETED PH.D. THESESon genetic
programming
* 58 STUDENTS WORKING ON THESISinvolving genetic
programming
* A PARTIAL LIST OF PEOPLEcompiled by
Bill Langdon who are active in genetic programming * INTERNATIONAL SOCIETY FOR GENETIC AND EVOLUTIONARY COMPUTATION (ISGEC) . ISGEC is the only membership organization in the field of genetic and evolutionary computation. It operates of the annual GECCO conference (largest conference in the field of genetic and evolutionary computation) and the biannual FOGAconference.
* EVO-NET
鈥擳he
Network of Excellence in Evolutionary Computation (an extensive clearinghouse of information about the field of genetic and evolutionary computation and operator of the annual Euro-GP conferences and the Evo-Net workshops) * The GA ARCHIVES , including back issues of the GA-Digest and EC-Digest, genetic algorithm code in various programming languages, an extensive list of conference announcements in the field of genetic and evolutionary computation,etc.
* BOOK SERIES OF GENETIC PROGRAMMINGfor Kluwer Academic
Publishers book series on genetic programming, edited by John R. Koza * BOOK SERIES ON GENETIC ALGORITHMS AND EVOLUTIONARY COMPUTATION _from Kluwer Academic Publishers, edited by David E. Goldberg._ * COURSES (AND SHORT COURSES) AT VARIOUS UNIVERSITIES ON GENETIC ALGORITHMS, GENETIC PROGRAMMING, AND EVOLUTIONARY COMPUTATION * For information about John Koza鈥檚 COURSE ON GENETIC ALGORITHMS AND GENETIC PROGRAMMING AT STANFORD UNIVERSITY * 11 BOOKS OF STUDENT PAPERSfrom John
Koza's Courses at Stanford University on genetic algorithms and genetic programming and artificial life* 6 COURSE READERS
from John
Koza's courses at Stanford University on genetic algorithms and genetic programming and artificial life * JOHN KOZA'S HOME PAGE AT STANFORD UNIVERSITY * For 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 MACHINEINTELLIGENCE _.
Click here to read CHAPTER 1 OF _GENETIC PROGRAMMING IV_ BOOK (2003)IN PDF FORMAT.
* 36 HUMAN-COMPETITIVE RESULTS PRODUCED BY GENETIC PROGRAMMING, including
21 previously patented inventions replicated by genetic programming and 2 patentable new inventions generated by genetic programming. * Link to HTTP://WWW.GENETIC-PROGRAMMING.COM (鈥済enetic-programming.COM鈥 WITH the hyphen) (Genetic Programming Inc.) including information about 1,000-Pentium parallel computer for doing genetic programmingresearch.
* JOBS
for scientific research programmer at Genetic Programming Inc. * Link to JAIME FERNANDEZ鈥橲 GENETIC PROGRAMMING NOTEBOOKsite
(鈥済eneticprogramming.com鈥 WITHOUT the hyphen) * DAVID BEASLEY鈥橲 FREQUENTLY ASKED QUESTIONS ABOUT GENETIC AND EVOLUTIONARY COMPUTATION . This comes in 6 parts. Part 2 has a summary of the different types of genetic and evolutionary computation. ------------------------- CONFERENCES ABOUT GENETIC PROGRAMMING (GP) AND GENETIC AND EVOLUTIONARY COMPUTATION (GEC) * Annual 2005 GENETIC AND EVOLUTIONARY COMPUTATION (GECCO) CONFERENCE to be held on June 25鈥29, 2005 (Saturday 鈥 Wednesday) in Washington DC. GECCO is the largest conference in the field of genetic and evolutionary computation. The GECCO-2005 conference is a combination of the 10th annual Genetic Programming Conference (GP-2005) and the 14th International Conference on Genetic Algorithms (ICGA-2005). GECCO is operated by the International Society for Genetic and Evolutionary Computation (ISGEC ). * Annual 2005 EURO-GENETIC-PROGRAMMING CONFERENCE (AND THE CO-LOCATED EVOLUTIONARY COMBINATORIAL OPTIMIZATION CONFERENCE AND OTHER EVO-NET WORKSHOPS) to be held on March 30 鈥 April 1, 2005 (Wednesday-Friday) in Lausanne,Switzerland.
* Annual NASA/DOD CONFERENCE ON EVOLVABLE HARDWARE (EH) to be held on June 24 鈥 26 (Thursday 鈥 Saturday), 2004 in Seattle. * GENETIC PROGRAMMING THEORY AND PRACTICE (GPTP) WORKSHOPSat the
University of Michigan in Ann Arbor in 2003 and 2004 and 2005 GENETIC PROGRAMMING THEORY AND PRACTICE (GPTP) WORKSHOPto be held at the
University of Michigan in Ann Arbor * 2004 ASIA-PACIFIC WORKSHOP ON GENETIC PROGRAMMING (ASPGP) held in Cairns, Australia on December 6-7 (Monday-Tuesday), 2004 * PAST GP CONFERENCES For 1996,
1997, and 1998 (including the SGA-98, the Symposium on GeneticAlgorithms)
* PAST EURO-GP CONFERENCESfor
1998, 1999, 2000, 2001, 2002, and 2003 * PAST GECCO CONFERENCES(Genetic
and Evolutionary Computation Conferences) for 1999, 2000, 2001, 2002, 2003, and 2004. Starting in 1999, the annual GECCO conference includes the annual Genetic Programming Conference. * ABOUT TWO DOZEN CONFERENCES WITH PUBLISHED PROCEEDINGSthat are held
regularly in the field of genetic programming and genetic and evolutionary computation (GEC) ------------------------- APPLICATION AREAS FOR GENETIC PROGRAMMING There are numerous applications of genetic programming. We are particularly interested in applying genetic programming to * 鈥淏LACK ART PROBLEMS,鈥 such as the automated synthesis of analog electrical circuits, controllers, antennas, networks of chemical reactions, optical systems, and other areas of design, * 鈥淧ROGRAMMING THE UNPROGRAMMABLE鈥 (PTU) involving the automatic creation of computer programs for unconventional computing devices such as cellular automata, multi-agent systems, parallel programming systems, field-programmable gate arrays, field-programmable analog arrays, ant colonies, swarm intelligence, distributed systems, and thelike, and
* COMMERCIALLY USEFUL NEW INVENTIONS (CUNI) involving the use of genetic programming as an automated "invention machine" for creating commercially usable new inventions. We are constantly looking for new domain areas in which to apply the techniques of genetic programming to achieve human-competitive machineintelligence.
------------------------- NEWS ABOUT GENETIC PROGRAMMING For May 2003 _IEEE Intelligent Systems_ article 鈥淲hat鈥檚 AI done for me lately? Genetic programming鈥檚 human-competitive results鈥, visit IEEE INTELLIGENT SYSTEMS . Click here for PDF FILE. For February 2003 _Scientific American_ article 鈥淓volving inventions鈥 on genetic programming by John Koza, Martin A. Keane, and Matthew J. Streeter, visit SCIENTIFIC AMERICAN. For SALON ARTICLE ON "SOFTWARE THAT WRITES SOFTWARE" By
Alexis Willihnganz (August 10, 1999) For E. E. TIMES ARTICLE ON AUTOMATIC SYNTHESIS OF ANALOG ELECTRICAL CIRCUITS USING GENETIC PROGRAMMING. For article in _COMPUTERBITS_on
genetic programming. For _SCIENTIFIC AMERICAN ARTICLE BY W. WAYT GIBBS_on
genetic programming. For _Business Week_ ARTICLE (JUNE 23, 1997)entitled
"Stanford Eggheads and Entrepreneurs" For _Business Week_ ARTICLE (AUGUST 25, 1997)entitled
"What Matters is How Smart You Are" For _U. S. NEWS AND WORLD REPORT_article
on evolutionary computation and genetic programming.For _SLASHDOT.ORG
_posting
(August 10, 1999).
For _THE451.COM
_article
entitled "Re-inventing the 'invention machine" (April 14, 2000). ------------------------- PARALLELIZATION OF GENETIC PROGRAMMING In July 1999, Genetic Programming Inc. started operating a new 1,000-node Beowulf-style parallel cluster computer consisting of 1,000 Pentium II 350 MHz processors and a host computer. Click here for technical discussion of PARALLEL GENETIC PROGRAMMINGand building the
1,000-PENTIUM BEOWULF-STYLE PARALLEL CLUSTER COMPUTER. About half of
the 36 HUMAN-COMPETITIVE RESULTS PRODUCED BY GENETIC PROGRAMMINGwere
obtained using computing systems that were _substantially smaller_ than the 1,000-Pentium computer mentioned above. Fifteen of these human-competitive results were obtained on a 1995-vintage parallel computer system composed of 64 PowerPC 80 MHz processors with a spec95fp rating. This 1995-vintage computer has total computational power equal to only about 1/60 of that of the 1000-Pentium machine mentioned above. Five of these results were obtained on a 70-Alpha machine (whose spec95fp rating is 1/9 of that of the 1,000-Pentium machine mentioned above). One of these human competitive results were obtained with a 1994-vintage machine (whose spec95fp rating is 1/1,320 of that of the 1,000-Pentium machine mentioned above). The individual processors in the1,000-Pentium machine have (as of July 2003) about 1/8 the speed of processors contained in commercially available $999 laptops, so that the 1,000-Pentium machine is approximately equivalent to a 125-processor machine with 2003-vintage processors. 1000-PENTIUM BEOWULF-STYLE CLUSTER COMPUTER (LEFT AND RIGHT SIDES) (JULY 29, 1999) For PICTURE OF UNINTERRUPTABLE POWER SUPPLY(UPS) for new
1000-Pentium computer. Design and contracting of site for 1000-Pentium computer by GORDON PRILL INC . of Mountain View, California. The 1,000-Pentium machine was assembled by Stan Fox of the COMPAQ Sunnyvale Staging Center. For picture of earlier 70-node parallel computer with SENATOR BARBARA BOXER (California), John Koza (back row), Oscar Stiffelman (front row), Forrest H Bennett III, and William Mydlowec. For picture of earlier 70-node parallel computer with ELLEN GOLDBERG (PRESIDENT OF SANTA FEINSTITUTE)
, John
Koza, Forrest H Bennett III, and Oscar Stiffelman. ------------------------- JOHN KOZA鈥橲 PUBLICATIONS ON GENETIC PROGRAMMING * 1992 BOOK ON GENETIC PROGRAMMING ENTITLED _GENETIC PROGRAMMING: ON THE PROGRAMMING OF COMPUTERS BY MEANS OF NATURAL SELECTION_FROM THE MIT
PRESS. THE MIT PRESS ALSO PUBLISHES A VIDEOTAPE ENTITLED _GENETIC PROGRAMMING: THE MOVIE _ASSOCIATED WITH THE FIRST BOOK. CLICK HERE FOR MORE INFORMATION ABOUT THIS 1992 VIDEOTAPE.
* 1994 BOOK ON GENETIC PROGRAMMING ENTITLED 聽_GENETIC PROGRAMMING II: AUTOMATIC DISCOVERY OF REUSABLE PROGRAMS_from The MIT
Press.
The MIT Press also publishes a videotape entitled _Genetic Programming II Videotape: The Next Generation._ associated with this second book. Click here for additional information about this 1994 VIDEOTAPE.
* 1999 BOOK _GENETIC PROGRAMMING III: DARWINIAN INVENTION ANDPROBLEM SOLVING_
FROM MORGAN KAUFMANN (BY JOHN R. KOZA, FORREST H BENNETT III, DAVID ANDRE, AND MARTIN A. KEANE). MORGAN KAUFMANN ALSO PUBLISHES _GENETIC PROGRAMMING III VIDEOTAPE: HUMAN-COMPETITIVE MACHINE INTELLIGENCE _(BY JOHN R. KOZA, FORREST H BENNETT III, DAVID ANDRE, MARTIN A. KEANE, AND SCOTT BRAVE). CLICK HERE FOR INFORMATION ABOUT THIS 1999 VIDEOTAPE.
* 2003 BOOK _GENETIC PROGRAMMING IV: ROUTINE HUMAN-COMPETITIVE MACHINE INTELLIGENCE_ FROM KLUWER
ACADEMIC PUBLISHERS (BY JOHN R. KOZA, MARTIN A. KEANE, MATTHEW J. STREETER, WILLIAM MYDLOWEC, JESSEN YU, AND GUIDO LANZA ) (ISBN 1-4020-7446-8) KLUWER ACADEMIC PUBLISHER ALSO PUBLISHES A DVD DISK _GENETIC PROGRAMMING IV: VIDEO: ROUTINE HUMAN-COMPETITIVE MACHINE INTELLIGENCE_ (BY JOHN R. KOZA, MARTIN A. KEANE, MATTHEW J. STREETER, WILLIAM MYDLOWEC, JESSEN YU, GUIDO LANZA, AND DAVID FLETCHER) THAT IS BOUND INTO THIS 2003 BOOK. * STANFORD UNIVERSITY TECHNICAL REPORTS FROM THE COMPUTER SCIENCE DEPARTMENT AND STANFORD BIOMEDICAL INFORMATICS OF WHICH I AM AUTHOR OR CO-AUTHOR CAN BE OBTAINED ON THE WEB, INCLUDING* STAN-TR-CS 1314
(1990) ENTITLED _GENETIC PROGRAMMING: A PARADIGM FOR GENETICALLY BREEDING POPULATIONS OF COMPUTER PROGRAMS TO SOLVE PROBLEMS _* STAN-TR-CS 1528
(1994)
ENTITLED _ARCHITECTURE-ALTERING OPERATIONS FOR EVOLVING THE ARCHITECTURE OF A MULTI-PART PROGRAM IN GENETIC PROGRAMMING _* STAN-TR-CS 1542
(1995)
ENTITLED _PARALLEL GENETIC PROGRAMMING ON A NETWORK OF TRANSPUTERS _* SMI-95-0586
(1995) ENTITLED _A PROGRAMMING COURSE IN BIOINFORMATICS FOR COMPUTER AND INFORMATION SCIENCE STUDENTS _* SMI-2000-0851
(2000) ENTITLED _REVERSE ENGINEERING AND AUTOMATIC SYNTHESIS OF METABOLIC PATHWAYS FROM OBSERVED DATA USING GENETIC PROGRAMMING_ * ABSTRACTS, CITATIONS, AND COPIES OF RESEARCH PAPERS (ALMOST ALL AVAILABLE IN POST SCRIPT OR PDF) BY JOHN KOZA:* 1972
* 1988
* 1989
* 1990
* 1991
* 1992
* 1993
* 1994
* 1995
* 1996
* 1997
* 1998
* 1999
* 2000
* 2001
* 2002
* 2003
* 2004
CLICK HERE FOR LIST OF PATENTS -------------------------CONTACT INFORMATION
Please send corrections or additions to this page to:JOHN R. KOZA
Genetic Programming Inc. (Third Millennium On-Line Products Inc.)Post Office Box K
Los Altos, California 94023 USAFAX: 650-941-9430
E-mail: KOZA@GENETIC-PROGRAMMING.COM E-mail: KOZA@GENETIC-PROGRAMMING.ORG ------------------------- For information about the annual Genetic and Evolutionary Computation Conference (GECCO) operated by the ASSOCIATION FOR COMPUTING SPECIAL INTEREST GROUP ON GENETIC AND EVOLUTIONARY COMPUTATION (SIGEVO) For information about the annual HUMAN-COMPETITIVE AWARDS (THE 鈥淗UMIES鈥) in genetic and evolutionary computation offered at the annual Genetic and Evolutionary Computation Conference (GECCO) The home page of Genetic Programming Inc. at WWW.GENETIC-PROGRAMMING.COM . The home page of JOHN R. KOZA (including online versions of most published papers) For information about John Koza鈥檚 COURSE ON GENETIC ALGORITHMS AND GENETIC PROGRAMMING AT STANFORD UNIVERSITY For information about NATIONAL POPULAR VOTE 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 MACHINEINTELLIGENCE _.
Click here to read CHAPTER 1 OF _GENETIC PROGRAMMING IV_ BOOK IN PDFFORMAT.
4,000+ 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鈥檚 and Steven M. Gustafson. For information on the GENETIC PROGRAMMING AND EVOLVABLE MACHINESJOURNAL
For information on the Genetic Programming book series, see the CALL FOR BOOK PROPOSALS -------------------------Details
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