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Abstract: A central problem in the theory of genetic algorithms is the characterization of problems that are difficult for GAs to optimize. Many attempts to characterize such problems focus on the notion of Deception, defined in terms of the static average fitness of competing schemas. This article examines the Static Building Block Hypothesis (SBBH), the underlying assumption used to define Deception. Exploiting contradictions between the SBBH and the Schema Theorem, we show that Deception is neither... (Update)
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BibTeX entry: (Update)
Grefenstette, J.J. (1992). Deception considered harmful. Foundations of Genetic Algorithms, 2. Whitley, L. D., (ed.), Morgan Kaufmann, 75--91. http://citeseer.ist.psu.edu/grefenstette92deception.html More
@incollection{ grefenstette93deception,
author = "John J. Grefenstette",
title = "Deception Considered Harmful",
booktitle = "Foundations of Genetic Algorithms 2",
publisher = "Morgan Kaufmann",
address = "San Mateo, CA",
editor = "L. Darrell Whitley",
pages = "75--91",
year = "1993",
url = "citeseer.ist.psu.edu/grefenstette92deception.html" }
Citations (may not include all citations):1931 Adaptation in natural and artificial systems (context) - Holland - 1975
192 Analysis of the behavior of a class of genetic adaptive syst.. (context) - De Jong - 1975
129 Messy genetic algorithms: Motivation (context) - Goldberg, Korb et al. - 1989
93 Modeling genetic algorithms with Markov chains (context) - Nix, Vose - 1992
72 Go to statement considered harmful (context) - Dijkstra - 1968
67 Genetic algorithms and Walsh functions: Part (context) - Goldberg
61 Genetic algorithms and Walsh functions: Part II (context) - Goldberg
55 How genetic algorithms work: An critical look at implicit pa.. (context) - Grefenstette, Baker - 1989
53 San Mateo (context) - the, Conference et al. - 1990
51 Genetic algorithms as function optimizers (context) - Bethke - 1981
51 Fundamental principles of deception in genetic search - Whitley - 1991
43 Messy genetic algorithms revisited: Studies in mixed size an.. (context) - Goldberg, Deb et al. - 1990
36 An analysis of multi-point crossover - Spears, De Jong - 1991
35 Simple genetic algorithms and the minimal deceptive problem (context) - Goldberg - 1987
28 What makes a problem hard for a genetic algorithms (context) - Forrest, Mitchell - 1993
26 Genetic algorithms and the variance of fitness - Goldberg, Rudnick - 1988
20 Real-coded genetic algorithms (context) - Goldberg - 1991
17 Don't worry (context) - Goldberg, Deb et al. - 1991
17 Isomorphisms of genetic algorithms (context) - Battle, Vose - 1991
16 The nonuniform Walsh-schema transform (context) - Bridges, Goldberg - 1991
14 Accounting for noise in the sizing of populations (context) - Goldberg, Deb et al. - 1992
5 dominance and implicit parallelism in genetic search (context) - Whitley - 1992
5 Analysing deception in trap functions (context) - Deb, Goldberg - 1992
3 Analysis and design of a general GA deceptive problem (context) - Homaifar, Qi et al. - 1991
3 The only challenging problems are deceptive (context) - Das, Whitley - 1991
3 Construction of high-order deceptive functions using low-ord.. (context) - Systems, Goldberg - 1992
2 Genetic algorithms are NOT function optimizers (context) - dissertation, Computer et al. - 1992
2 Representational issues in genetic algorithms (context) - Liepins, Vose - 1990
2 Genetic algorithms in search (context) - Davis, Genetic et al.
1 GA-easy does not imply steepest-ascent optimizable Proceedin.. (context) - Mathematics, Intelligence et al. - 1991
1 Deceptiveness and genetic algorithm dynamics (context) - Theor, Liepins et al. - 1991
1 Genetic algorithms and their applications (context) - Systems, Grefenstette - 1990
1 Also available as Oregon Graduate Institute Technical Report.. (context) - Mathematics, Intelligence et al. - 1991
1 Conditions for implicit parallelism (context) - Eds, York et al. - 1991
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