Making It To The Most Read Articles Lists in 2009

The Paper “Search, Neutral Evolution, and Mapping in Evolutionary Computing: A Case Study of Grammatical Evolution” Wilson, D.   Kaur, D.,  appeared in the July 2009 Top 10 Downloads of the IEEE Transactions on Evolutionary Computing ranked #1.

It also appeared (ranked #27) in the Top 100 Downloads of the entire IEEExplore site for July 2009!

Not bad!

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For Your Viewing Pleasure

Below is the first of a series of lectures on Evolution, Ecology and Behavior by Professor Stearns of Yale University.

It has a lot of material that should be of interest to anyone interested in Evolutionary Computing. The fourth video in the series is on neutral evolution and genetic drift.

This series is going to make up a good portion of my holiday viewing.

MLK Day on Monday, then Obama’s inauguration on Tuesday.

Living the Dream, President Barack Obama, Dr. ...
Image by BL1961 via Flickr

Martin Luther King’s Day on Monday, then Obama’s inauguration on Tuesday; could you have arranged it any better?

I am looking forward to Tuesday’s inauguration poem, which is authored (and will be recited) by the highly accomplished poet Elizabeth Alexander.

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Search, Neutral Evolution and Mapping in Evolutionary Computing:2

Here is a pre-proof copy of my accepted paper: “Search, Neutral Evolution and Mapping in Evolutionary Computing: A Case Study of Grammatical Evolution”.

I would encourage you to read section X  (Analysis of related works) , to see its true implications.

I plan to do a series of posts on what this paper means for Evolutionary Computing, and to post some of the MATLAB code used in this work.

You might want to subscribe to my RSS feed.

“This paper is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.”


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Search, Neutral Evolution and Mapping in Evolutionary Computing: A Case Study of Grammatical Evolution

The above is the title of my paper that has been accepted by IEEE Trans. on Evolutionary Computing. My doctoral supervisor Dr Kaur is a coauthor of the paper.

Here is the abstract:

We present a new perspective of search in Evolutionary Computing (EC) by using a novel model for the analysis and visualization of genotype to phenotype maps. The model groups genes into quotient sets and shows their adjacencies. A unique quality of the quotient model is that it details geometric qualities of maps that are not otherwise easy to observe. The model shows how random mutations on genes make non-random phenotype preferences, based on the structure of a map. The interaction between such mutation-based preferences with fitness preferences is important for explaining population movements on neutral landscapes. We show the widespread applicability of our approach by applying it to different representations, encodings and problems including Grammatical Evolution (GE), Cartesian Genetic Programming, Parity and Majority Coding, OneMax, Needle-in-Haystack, Deceptive Trap and Hierarchical if-and-only-if. We also use the approach to address conflicting results in the neutral evolution literature and to analyze concepts relevant to neutral evolution including robustness, evolvability, tunneling and the relation between genetic form and function.

We use the model to develop theoretical results on how mapping and neutral evolution affects search in GE. We study the two phases of mapping in GE; these being transcription (i.e. unique identification of genes with integers), and translation (i.e. many-to-one mapping of genotypes to phenotypes). It is shown that translation and transcription schemes belong to equivalence classes, therefore the properties we derive for specific schemes are applicable to classes of schemes. We present a new perspective on population diversity. We specify conditions under which increasing degeneracy (by increasing codon size) or rearranging the rules of a grammar do not affect performance. It is shown that there is a barrier to nontrivial neutral evolution with the use of the natural transcription with modulo translation combination; a necessary but not sufficient condition for such evolution is at least three bits should change on mutation within a single codon. This barrier can be avoided by using Gray transcription. We empirically validate some findings.

This paper was originally written with a more modest scope limited to Grammatical Evolution (which was a central part of my dissertation). If it seems overachieving it is partly due to me and partly due to reviewer requests for a more general approach. The amount of work behind this paper is painful to even think of. I am not complaining though, the final product is certainly worth the effort and I am very satisfied at the quality.

Please email me if you want to see a draft copy.

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