Talk:Evolution strategy

message: One should add the original papers, not just the recent surveys.
After all, these are the first serious applications of artificial evolution:
Ingo Rechenberg (1971): Evolutionsstrategie - Optimierung technischer Systeme
nach Prinzipien der biologischen Evolution (PhD thesis).
Reprinted by Fromman-Holzboog (1973).
Hans-Paul Schwefel (1974): Numerische Optimierung von Computer-Modellen (PhD thesis).
Reprinted by by Birkhäuser (1977).
Algorithms 13:13, 2 June 2007 (UTC)
thread_title:  Original References 

message: It appears that the word Bionics is used commonly on the external links to German institutions, but the definition on the wiki and commonly used in English isn't entirely related to the specific use of an algorithm like this?! I've removed the see also link to the page, if anyone has a strong reason why I'm wrong just leave me some stuff on my Talk page :) 
:"Bionics: Study of the results of biological evolution from the engineering point of view."  That's more like biologically inspired engineering which doesn't have a great deal to do with a form of evolutionary algorithm which can be applied to any kind of problem where the solution space is large, it doesn't have to be a biologically inspired problem or solution. Ultima 13:59, 9 November 2006 (UTC)
thread_title:  Use of Bionics? 

message: Could you say where you found that
Contemporary derivatives of evolution strategy often use a population of μ parents and also recombination as an additional operator (called (μ/ρ+,λ)-ES). This is believed to make them less prone to get stuck in local optima. Because of using recombination, these algorithms might also be classified as real-coded genetic algorithms.?
If you have some reference (paper) to justify that argument, please, show us. :)
The first point that should be noticed is related to the selection schemes applied in Genetic Algorithms (GAs) and those used in Evolution Strategies (ESs). In GAs, the selection scheme applied to select the individuals which will be evolved usually is fitness based (tournament, roulette, etc), but in ESs all individuals are evolved, even those that are not so fit.
I consider that argument (bold text) is incorrect because ES has a very particular kind of recombination operators, which even have convergence and progress rate analysis. However, inside GA field there are not recombination operators like those.
And more: In ES the evolutionary process happens in the order recombination-mutation-selection, while in GA it is selection-recombination-mutation. Traditionally, the recombination operator is the major one in GAs, while in ESs that role is played by the mutation operator.
An important point: In ES, the recombination operator can work with 1 \le \rho \le \mu. 
What means that from 1 up to μ individuals can be involved in crossover to produce just one offspring. In binary GA, there are generally 2 chromossomes that generate 2 offsprings. So, here we have another difference between GA and ES. Also, in ES all μ parent individuals can be mutated and recombinated, while in GAs some parents are not selected to be evolved by the evolution process, that is, by the evolutionary operators.
Another point that should be considered is the fact that Evolution Strategies use the self-adaptation mechanism to tune its parameters, while in Genetic Algorithms we do not have that kind of adaptation.
There were some critiques about using real-coded GA (big alphabets), because binary representation help[s] convince us of the greater information that becomes available using smaller alphabets (Goldberg, Real-coded genetic algorithms virtual alphabets and blocking, 1990, pp 4). Although also there are some critiques related to GAs, both real- and binary-coded ("Reevaluating Genetic Algorithm Performance under Coordinate Rotation of Benchmark Functions; A survey of some theoretical and practical aspects of genetic algorithms." BioSystems, 39(3):263-278, 1996, Elsevier Science.). But these latter ones are quit a bit "unpopular".
So, after all those points I listed and explained, I consider that would be sensible to delete that part of the text that says recombinative evolution strategies might be classified as real-coded genetic algorithms.
If someone has some critique about what I wrote, please, tell me. :)
References
*K. A. De Jong and J. Sarma: "Generation gaps revisited ", Foundations of Genetic Algorithms 2, Morgan Kaufmann, pp. 19--28 (1993).
* H.-G. Beyer and H.-P. Schwefel. Evolution Strategies: A Comprehensive Introduction. Journal Natural Computing, 1(1):3-52, 2002.
*Goldberg D. E., Real-coded genetic algorithms virtual alphabets and blocking, 1990.
*Ralf Solomon, Reevaluating Genetic Algorithm Performance under Coordinate Rotation of Benchmark Functions; A survey of some theoretical and practical aspects of genetic algorithms. BioSystems, 39(3):263-278, 1996, Elsevier Science.
Nosophorus 18:36, 11 November 2006 (UTC)
thread_title:  Recombinative ES == Real Coded GA? 

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