Thursday, October 28, 2010

Old School Genetic Algorithms News On Google News Archive

Interesting feature this one from Google News. You can browse old newspapers and read old news.

Looking for genetic algorithms, Google News Archive gives you a nice amount of news dating back to 1980s.

For example, see this simulated annealing news on the excellent magazine Dr. Dobbs -- genetic algorithms and other optimization approaches are cited and/or briefly explained. It's from 1989.

This other one is a brief summary of students and researchers work on engineering mentioning genetic algorithms and the early work of David E. Goldberg during his good times at The Clearing House For Genetic Algorithms. The excerpt:


James Gleick wrote an article on artificial life during its early steps, citing genetic algorithms along the way.

And this another one suggests someone was, as early as 1983, already using genetic algorithms to do stock trading or something related.

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Thursday, March 25, 2010

An Old School Genetic Algorithm News



Interesting finding this one! Just click on the picture above and read the news! It's from 1986 and published on Tuscaloosa News. I think it summarizes some aspects of the good times at The Clearing House for Genetic Algorithms. Very old school, indeed.

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Saturday, December 12, 2009

A Nice Genetic Algorithm Lecture

Professor David Edward Goldberg (@deg511) delivered a nice lecture on genetic algorithms in which he shares his views on them.

Here you are the lecture in four parts:

Part 1

Part 2

Part 3

Part 4

I have not seen everything yet. As soon as I have done it, I'll share my views on the lecture.

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Thursday, February 12, 2009

A Nice Evolutionary Computation Year



This year, 2009, is full of nice dates to be celebrated!

Today is the birthday of Charles Darwin, the scientist who began evolutionary biology as we know it today. It's Darwin's 200th annivesary.

Also, this year it will be completed 150 years since the publication of a seminal book and one of the most influential along all the human history: On the Origin of Species.

Its contribution to our biological world understanding is tremendous, of course it left for a time so many gaps that Darwin was unable to give the correct and complete answers, but its merits overcast any imperfection it may have.



Another interesting date sends us back to 45 years ago: 1964. The destination is Germany and its beautiful capital city: Berlin. There, a seasoned senior student Ingo Rechenberg and a newbie Hans-Paul Schwefel are about to produce the first results that would pave the way for a branch of evolutionary computation: Evolution Strategies (or Evolutionsstrategie, in German). A crude, simple and -- why not? -- elegant experiment takes place. Its results would show both students the method could be worth to be worked on.


Now, let's jump 25 five years into the future. The year is 1989. An enthusiastic professor from the University of Alabama releases his first book which would set the stage in the near future for so many debates around evolutionary computation, evolutionary algorithms and, of course, genetic algorithms themselves. The book would become an evolutionary computation classic by its own merits, making the fine art of genetic algorithms reachable and, more important, understandable for the large wide audience out there. It was in this book that scientists, practioners, students, and professors had their first contacts with genetic algorithms and evolutionary computation, being hard to find nowadays someone who implemented a genetic algorithm without having heard and/or read the pages of Genetic Algorithms in Search, Optimization, and Machine Learning. Of course, it is impossible to publish something expecting everyone will agree with your ideas and that book has found so many readers along the time having each one a critique view about it. Be the critiques for praise or not, it is difficult not to tell the importance such a book (has) had inside evolutionary computation. But, something is very hard to deny: That is a great book to read. Despite some small imperfections the reader gets what the book promises: A nice introduction to genetic algorithms and enough understanding to code one in computer programming language.

The way Professor David Edward Goldberg teaches the reader is very instructive and clarifying. He even simulates by hand a simple step of a genetic algorithm.

This year is a year of celebration for all of us who had/have a contact with evolutionary ideas. Let's praise and thank all those persons who invested a nice amount of the time of their lives helping to build the fields in which so many researchers, students, and so on have followed since then.

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