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Abstract: At the previous FOGA workshop, we presented some initial results on using Markov models to analyze the transient behavior of genetic algorithms (GAs) being used as function optimizers (GAFOs). In that paper, the states of the Markov model were ordered via a simple and mathematically convenient lexicographic ordering used initially by Nix and Vose. In this paper, we explore alternative orderings of states based on interesting semantic properties such as average fitness, degree of homogeneity,... (Update)
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...6.2. Timing Experiments. It is now necessary to examine the computational cost of the compression algorithm. Our prior work, 2] and [9], focused heavily on the insights gained by actually examining Q n u , which involved computations on the order of N 3 (to multiply Q u...
...of this technique for time varying data is to animate a parallel coordinate plot, redrawing the multidimensional points as they change over time. This has been especially useful in our investigations of how the column mass of a Markov chain of an EA changes over time ##CITE##(Spears and De...
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0.2: Aggregating Models of Evolutionary Algorithms - Spears (1999) (Correct)
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0.3: Using Markov Chains to Analyze GAFOs - De Jong, Spears, Gordon (1995) (Correct)
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2: Using Markov chains to analyze GAFOs - de Jong, Spears et al. - 1995
BibTeX entry: (Update)
W. Spears and K. De Jong, Analyzing GAs using Markov models with semantically ordered and lumped states. Foundations of GAs Workshop. Morgan Kaufmann, (1996), pp. 85 -- 100. http://citeseer.ist.psu.edu/spears96analyzing.html More
@incollection{ spears97analyzing,
author = "William M. Spears and Kenneth A. {De Jong}",
title = "Analyzing {GA}s Using Markov Models with Semantically Ordered and Lumped States",
booktitle = "{F}oundations of {G}enetic {A}lgorithms 4",
publisher = "Morgan Kaufmann",
address = "San Francisco, CA",
editor = "Richard K. Belew and Michael D. Vose",
pages = "85--100",
year = "1997",
url = "citeseer.ist.psu.edu/spears96analyzing.html" }
Citations (may not include all citations):276 Finite Markov Chains (context) - Kemeny, Snell - 1960
54 Modeling Simple Genetic Algorithms (context) - Vose - 1995
28 Modelling genetic algorithms with Markov chains (context) - Nix, Vose - 1992
24 Numerical experiments with iteration and aggregation for Mar.. - Stewart, Wu - 1992
17 Using Markov chains to analyze GAFOs - De Jong, Spears et al. - 1994
6 A compression algorithm for probability transition matrices - Spears - 1996
2 A survey of methods for computing large sparse matrix expone.. - Sidje, Stewart - 1996
1 Quasi-lumpability (context) - Dayar, Stewart - 1996
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