Chapter 13

[13:1] Adaptation in Natural and Artificial Systems: An introductory Analysis with Application to Biology, Control and Artificial Intelligence J. Holland –1992 MIT Press

[13:2] Genetic Algorithms in Search, Optimization and Machine Learning D. Goldberg - Addison-Wesley 1989

[13:3] What is Evolution? Stated Clearly – 2013 - http://www.youtube.com

[13:4] Complexity and Approximation: Combinatorial optimization problems and their approximability properties §Compendium of NP optimization problems G. Ausiello, P. Crescenzi, G. Gambosi, V. Kann, A Marchetti-Spaccamela, M. Protazi - 1999 - http://www.csc.kth.se/~viggo/wwwcompendium/

[13:5] Introduction to Evolutionary Computing §2 What is an Evolutionary Algorithm? A. Eiben, J.E. Smith – Springer 2003

[13:6] Machine Learning: A Probabilistic Perspective §16.6 Ensemble learning K. Murphy – MIT Press 2012

[13:7] Adaptation in Natural and Artificial Systems: An introductory Analysis with Application to Biology, Control and Artificial Intelligence §6 Reproductive Plans and Genetic Operators J. Holland –MIT Press 1992

[13:8] Introduction to Genetic Algorithms Tutorial IX Selection M. Obitko - http://www.obitko.com/tutorials/genetic-algorithms/selection.php

[13:9] Introduction to Genetic Algorithms -§Scaling of Relative Fitness E.D Goodman, - Michigan State University 2009 World Summit on Genetic and Evolutionary Computation, Shanghai - http://www.egr.msu.edu/~goodman/GECSummitIntroToGA_Tutorial-goodman.pdf

[13:10] The Lokta-Volterra equation: Wikipedia the free encyclopedia Wikimedia Foundation - http://en.wikipedia.org/wiki/Lotka-Volterra_equation

[13:11] A comprehensive Survey of Fitness Approximation in Evolutionary Computation Y. Jin - Honda Research Institute Europe 2003 - http://epubs.surrey.ac.uk/7610/2/SC2005.pdf

[13:12] Stock price prediction using genetic algorithms and evolution strategies G. Bonde, R. Khaled Institute of Artificial Intelligence - University of Georgia - http://worldcomp-proceedings.com/proc/p2012/GEM4716.pdf