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!
Posts Tagged ‘Evolutionary Computation’
Making It To The Most Read Articles Lists in 2009
Posted in Artificial intelligence, Evolutionary computing, Grammatical Evolution, Machine Intelligence, Machine Learning, Personal, tagged Genetic algorithm, Genetic Programming, Evolutionary Computation, IEEE Transactions on Evolutionary Computing, Search Theory, Extended Phenotype on December 21, 2009 | Leave a Comment »
For Your Viewing Pleasure
Posted in Artificial intelligence, Evolutionary computing, Grammatical Evolution, Machine Intelligence, Machine Learning, Personal, intelligent machines, tagged Evolution, Evolutionary Computation, Genetic drift, neutral evolution on December 12, 2009 | Leave a Comment »
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 [...]
Is Neutral Evolution Useful for Evolutionary Computation? Part I
Posted in Artificial intelligence, Evolutionary computing, Grammatical Evolution, Machine Intelligence, tagged Artificial intelligence, Evolution, Evolutionary Computation, Gene, Genetic algorithm, Genetic drift, Genetic Programming, Grammatical Evolution, neutral evolution, Phenotype on January 21, 2009 | 2 Comments »
Based on publications, and responses from reviewers on the subject, it is evident that neutral evolution is a misused and misunderstood concept in evolutionary computation circles. I intend to dispel some of the confusion in this series of post based on some material from a journal paper by Dr. Kaur (my doctoral supervisor) and myself [...]
Extending the Phenotype in Evolutionary Computing
Posted in Artificial intelligence, Evolutionary computing, Grammatical Evolution, intelligent machines, tagged Evolution, Evolutionary Computation, Extended Phenotype, Gene, Genetic Programming, Phenotype, Richard Dawkins on January 16, 2009 | Leave a Comment »
In his very readable book “The Extended Phenotype“, Dawkins defined the “Extended Phenotype” as the effects of a gene when those effects are not regarded as being confined to the individual body in which the gene sits. He argues against the arbitrariness of limiting the applicability of phenotypes only to expressions of an organism’s genes [...]
Search, Neutral Evolution and Mapping in Evolutionary Computing:2
Posted in Artificial intelligence, Evolutionary computing, Grammatical Evolution, Machine Learning, Personal, intelligent machines, tagged Artificial intelligence, Evolution, Evolutionary Computation, Genetic Programming, Grammatical Evolution, MATLAB, Paper, Search Theory on January 15, 2009 | Leave a Comment »
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, [...]
Some ways you can go wrong with Evol. Comp. II
Posted in Machine Learning, tagged Bean Machine, Evolutionary Computation, IEEE Transactions on Evolutionary Computing, Mutation, Normal distribution, Population, Randomness on October 11, 2008 | Leave a Comment »
Misunderstanding Randomness
There are two aspects of randomness in Evolutionary computing that are frequently misunderstood . The first issues is the assumption that the effects of random mutations are always random. No that is not a typo, the effects of random mutation are usually not random but are coordinated into nonrandom distributions based on how genes [...]
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