Behavioral Program Synthesis with Genetic Programming (Record no. 80298)

000 -LEADER
fixed length control field 04083nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-319-27565-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801222015.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151215s2016 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319275659
-- 978-3-319-27565-9
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Krawiec, Krzysztof.
245 10 - TITLE STATEMENT
Title Behavioral Program Synthesis with Genetic Programming
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XXI, 172 p. 25 illus., 15 illus. in color.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Program Synthesis -- Limitations of Conventional Program Evaluation -- The Framework of Behavioral Program Synthesis -- Behavioral Assessment of Test Difficulty -- Semantic Genetic Programming -- Synthesizing Programs with Consistent Execution Traces -- Pattern-guided Program Synthesis -- Behavioral Code Reuse -- Search Drivers -- Experimental Assessment of Search Drivers -- Implications of the Behavioral Perspective -- Future Perspectives.
520 ## - SUMMARY, ETC.
Summary, etc Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subscribing to that perspective to varying extent are presented and discussed, including implicit fitness sharing, semantic GP, co-solvability, trace convergence analysis, pattern-guided program synthesis, and behavioral archives of subprograms. The framework involves several concepts that are new to GP, including execution record, combined trace, and search driver, a generalization of objective function. Empirical evidence gathered in several presented experiments clearly demonstrates the usefulness of behavioral approach. The book contains also an extensive discussion of implications of the behavioral perspective for program synthesis and beyond. .
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-27565-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2016.
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-- txt
-- rdacontent
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-- computer
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-- rdamedia
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-- online resource
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-- text file
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Software engineering.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Software Engineering.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-9503 ;
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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