- 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, fitness testing, object orientated, 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://www.springer.com/gp/book/9780792381358",
-
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",
