Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming!

Created by W.Langdon from gp-bibliography.bib Revision:1.3332

@Book{langdon:book,
  author =       "William B. Langdon",
  title =        "Genetic Programming and Data Structures: Genetic
                 Programming + Data Structures = Automatic
                 Programming!",
  publisher =    "Kluwer",
  year =         "1998",
  volume =       "1",
  series =       "Genetic Programming",
  address =      "Boston",
  keywords =     "genetic algorithms, genetic programming, OOGP, data,
                 memory, stack, list, queue, Pareto multi-objective
                 fitness, analysis, Price's covariance selection
                 theorem",
  ISBN =         "0-7923-8135-1",
  email =        "kluwer@wkap.com",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/gpdata",
  URL =          "http://link.springer.com/book/10.1007/978-1-4615-5731-9/page/1",
  doi =          "doi:10.1007/978-1-4615-5731-9",
  notes =        "Computers that 'program themselves' has long been an
                 aim of computer scientists. Recently genetic
                 programming (GP) has started to show its promise by
                 automatically evolving programs. Indeed in a small
                 number of problems GP has evolved programs whose
                 performance is similar to or even slightly better than
                 that of programs written by people. The main thrust of
                 GP has been to automatically create functions. While
                 these can be of great use they contain no memory and
                 relatively little work has addressed automatic creation
                 of program code including stored data. It is this issue
                 which GENETIC PROGRAMMING AND DATA STRUCTURES
                 addresses. Motivated by the observation from software
                 engineering that data abstraction (e.g., via abstract
                 data types) is essential in programs created by human
                 programmers. This book will show that abstract data
                 types can be similarly beneficial to the automatic
                 production of programs using GP.

                 GENETIC PROGRAMMING AND DATA STRUCTURES shows how
                 abstract data types (stacks, queues and lists) can be
                 evolved using genetic programming, demonstrate GP can
                 evolve general programs which solve the nested brackets
                 problem, recognise a Dyck context free language and
                 implement a simple four function calculator. In these
                 cases an appropriate data structure is beneficial
                 compared to simple indexed memory. This book also
                 includes a survey of GP, including a critical review of
                 experiments with evolving memory and reports
                 investigations of real world electrical network
                 maintenance scheduling problems that demonstrate that
                 Genetic Algorithms can find low cost viable solutions
                 to such problems.

                 GENETIC PROGRAMMING AND DATA STRUCTURES should be of
                 direct interest to computer scientists doing research
                 on genetic programming, genetic algorithms, data
                 structures, and artificial intelligence. In addition,
                 this book will be of interest to practitioners working
                 in all of these areas and to those interested in
                 automatic programming.

                 Contents

                 Foreword by John R. Koza.

                 Preface. 1. Introduction. 2. Survey. 3. Advanced
                 Genetic Programming Techniques. 4. Evolving a Stack. 5.
                 Evolving a Queue. 6. Evolving a List. 7. Problems
                 Solved Using Data Structures. benchmarks:
                 http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/grammar_test_ilp.tar.gz

                 8. Evolution of GP Populations. 9.
                 Conclusions.

                 Appendices: A. Number of Fitness Evaluations Required.
                 B. Glossary. C. Scheduling Planned Maintenance of the
                 National Grid. D. Implementation. Index.

                 Kluwer Accademic Publishers, Order Dept., Box 358,
                 Accord Station, Hingham, MA 02018-0358, USA Tel: +1 781
                 871-6600 FAX: +1 781 871-6528

                 Tangent distribution of constants. reverse polish
                 notation calculator",
  size =         "292 pages",
}

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