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cs356:jason_duke

Jason's Abstract and Citations

Abstract

    Genetic algorithms are where biology meets computer science. They are programming techniques that mimic biological evolution as a problem-solving strategy.The input to the algorithm is a set of potential solutions to that problem, encoded in some fashion, and a metric called a fitness function that allows each candidate to be quantitatively evaluated. In my paper/presentation I plan to introduce GAs and their history, their strengths and weaknesses, provide an example of a problem and solution using a GA, and also other problem-solving techniques that function similarly to GAs.


Citations

Genetic Programming

Bibliography on GA

Genetic Algorithms: Principles and Perspectives

http://www.ai-junkie.com/ga/intro/gat1.html

http://www.talkorigins.org/faqs/genalg/genalg.html

http://www.genetic-programming.com/gpanimatedtutorial.html


Presentation

cs356/jason_duke.txt · Last modified: 2010/04/28 10:42 by jdfalcon06