Advances in genetic programming
Author(s)
Bibliographic Information
Advances in genetic programming
(Complex adaptive systems)(Bradford book)
MIT Press, c1994-
- [v. 1]
- v. 2
- v. 3
Available at / 90 libraries
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Ibaraki University Library, Hitachi Branch分
[v. 1]007.64:Adv:1111603217,
v. 3007.64:Adv:3111700608, v.2007.64:Adv:2219700394 -
Kanagawa Institute of Technology
1007.64||A12019415,
2007.64||A||212022692, 3007.64||A||312022195 -
Library, Research Institute for Mathematical Sciences, Kyoto University数研
1.C||Advances-||1594010285,
2.C||Advances-||15||296057145 -
Library, Faculty of Engineering, Kinki University図書館
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Vol.2007.64||A16||212015841 -
Kobe University Library for Science and Technology
[v. 1]548-2-274030309400990,
v. 2548-2-274//2030009607505, v. 3548-2-274//3030009906946 -
[v. 1]430||ADV-1||1H0009567,
v. 2430||ADV-1||2H0013099, v. 3430||ADV-1||3H0009568 OPAC
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Faculty of Textile Science and Technology Library, Shinshu University図
v. 2007.64:A 162810139697,
007.64:A162810084547 -
Institute of Science Tokyo Suzukakedai Library
[v. 1]007.64/A/1216254716,
v. 2007.64/A/2216421582 -
Doshisha University Library (Imadegawa)
[v. 1]007.64||K360||1046100048,
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[v. 1]549.92||A 1694200757,
v. 2549.92||A 16||296202360, v. 3549.92||A 16||3 -
Digital Library of Nara Institute of Science and Technology図
[v. 1]BD20||82||19111592,
v. 2BD20||82||29113796, v. 3BD20||82||39111594 -
Hokkaido University, Library, Graduate School of Science, Faculty of Science and School of Science図書
dc20:006.3/k6232070308491
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Note
Vol. 2: edited by Peter J. Angeline and Kenneth E. Kinnear, Jr.
Vol. 3: edited by Lee Spector ... [et al.]
Includes bibliographical references and indexes
[Vol. 1]: x, 518 p. : ill., c1994. v. 2: xv, 538 p, c1996. v. 3: ix, 476 p. : ill., c1999
Description and Table of Contents
- Volume
-
v. 2 ISBN 9780262011587
Description
Table of Contents
- Genetic programming's continued evolution, Peter J. Angeline. Part 1 Variations on the genetic programming theme: a comparative analysis of genetic programming, Una-May O'Reilly and Franz Oppacher
- evolving programmers - the co-evolution of intelligent recombination operators, Astro Teller
- extending genetic programming with recombinative guidance, Horishi Iba and Hugo de Garis
- two self-adaptive crossover operators for genetic programming, Peter J. Angeline
- explicitly defined introns and destructive crossover in genetic programming, Peter Nordin et al. Part 2 modular, recursive and pruning genetic programmes: simultaneous evolution of programmes and their control structures, Lee Spector
- classifying protein segments as transmembrane domains - using architecture-altering operations in genetic programming, John R. Koza and David Andre
- discovery of subroutines in genetic programming, Justinian P. Rosca and Dana H. Ballard
- evolving recursive programmes for tree search, Scott Brave
- evolving recursive functions for the even-parity problem using genetic programming, Man Leung Wong and Kwong Sak Leung
- adaptive fitness functions for dynamic growing/pruning of programme trees, Byoung-Tak Zhang and Heinz Muhlenbein. Part 3 Analysis and implementation issues in genetic programming: efficiently representing populations in genetic programming, Maarten Keijzer
- genetically optimizing the speed of programmes evolved to play tetris, Eric V. Siegel and Alexander D. Chaffee
- the royal tree problem, a benchmark for single and multiple population genetic programming, William F. Punch et al
- parallel genetic programming - a scalable implementation using the transputer network architcture, David Andre and John R. Koza
- massively parallel genetic programming, Hugues Juille and Jordan B. Pollack
- type inheritance in strongly typed genetic programming, Thomas D. Haynes et al
- on using syntactic constraints with genetic programming, Frederic Gruau
- data structures and genetic programming, William B. Langdon. Part 4 New environments for genetic programming: algorithm discovery using the genetic programming paradigm - extracting low-contrast curvilinear features from SAR images of Arctic ice, Jason M. Daida et al
- genetic programming learning and the cobweb model, Shu-Heng Chen and Chia-Hsuan Yeh
- evolutionary identification of macro-mechanical models, Marc Shoenauer et al
- discovering time oriented abstractions in historical data to optimize decision tree classification, Brij Masand and Gregory Piatetsky-Shapiro. Part 5 Appendices: genetic programming resources on the World-Wide Web, Patrick Tufts
- a bibliography for genetic programming, William B. Langdon.
- Volume
-
[v. 1] ISBN 9780262111881
Description
Table of Contents
- Part 1 Introduction: a perspective on the work in this book, Kenneth E. Kinnear
- introduction to genetic programming, John R. Koza. Part 2 Increasing the power of genetic programming: the evolution of evolvability in genetic programming, Lee Altenberg
- genetic programming and emergent intelligence, Peter J. Angeline
- scalable learning in genetic programming using automatic function definition, John R. Koza
- alternatives in automatic function definition - a comparison of performance, Kenneth E. Kinnear
- the Donut problem - scalability, generalization and breeding policies in genetic programming, Walter Alden Tackett and Aviram Carmi
- effects of locality in individual and population evolution, Patrik D'haeseleer and Jason Bluming
- the evolution of mental models, Astro Teller
- evolution of obstacle avoidance behaviour - using noise to promote robust solutions, Craig W. Reynolds
- pygmies and civil servants, Conor Ryan
- genetic programming using a minimum description length principle, Hitoshi Iba et al
- genetic programming in C++ - implementation issues, Mike J. Keith and Martin C. Martin
- a compiling genetic programming system that directly manipulates the machine code, Peter Nordin. Part 3 Innovative applications of genetic programming: automatic generation of programs for crawling and walking, Graham Spencer
- genetic programming for the acquisition of double auction market strategies, Martin Andrews and Richard Prager
- two scientific applications of genetic programming - stack filters and non-linear equation fitting to chaotic data, Howard Oakley
- the automatic generation of plans for a mobile robot via genetic programming with automatically defined functions, Simon G. Handley
- competitively evolving decision trees against fixed training cases for natural language processing, Eric V. Siegel
- cracking and co-evolving randomizers, Jan Jannink
- optimizing confidence of text classification by evolution of symbolic expressions, Brij Masand
- evolvable 3D modelling for model-based object recognition systems, Thang Nguyen and Thomas Huang
- automatically defined features - the simultaneous evolution of 2-dimensional feature detectors and an algorithm for using them, David Andre
- genetic micro programming of neural networks, Frederic Gruau.
- Volume
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v. 3 ISBN 9780262194235
Description
by "Nielsen BookData"