Talk:Gaussian adaptation

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A more comprehensive outline on Gaussian adaptation may be found on my web site http://www.evolution-in-a-nutshell.se

Kjells 19:40, 30 January 2007 (UTC)

Question removed --Kjells 06:55, 31 March 2007 (UTC)

Contents 1 Original research/unverified claims? 2 Improvements have been made 3 About the conflict of interest 4 creationists have reason to doubt the classical teory of evolution 5 Gaussian adaptation used for other purposes

[edit] Original research/unverified claims?

Does this count as original research or not? That is a tricky question. The author is published, but the articles are minimally cited and discussed according to research databases. The author describes his theories relating to evolution as "alternative" sv:Diskussion:Socialdarwinism (as user Rogerg) [[1]] (as user gregor). I think the answer is yes, it is OR, mainly because there are really no independent sources that discuss or support the claims that are made. Sjö 14:57, 19 April 2007 (UTC)

Some figures in the link to evcforum above are now visible again.--Kjells 12:03, 23 April 2007 (UTC)

[edit] Improvements have been made

The only”research” made by me concerns two mathmatical theorems. The theorem of Gaussian adaptation (here abbreviated GA) was discovered 1969 at random, see http://www.evolution-in-a-nutshell.se/background.htm. Information theory was used already in 1969, but the theorem of efficiency – based on information content was discovered later, in 1991. The rest is more like discovering that 1 + 1 = 2, using results that are well known, cited and discussed.

I admit that there are unverified claims, so I have tried to fill the gaps by adding references to: Hartl, Kandel et al., Kirkpatrick, Levine, MacLean, Maynard Smith, Mayr and Zohar. Some other improvements has also been made. For instance, in order to avoid self-assertion, my name has been removed from the ingress. But some references must be made to our papers.

I admit that very few authors cite or discuss our work. The only technical paper and dissertation are due to Pinel & Singhal and Stehr. Pinel & Singhal writes 1981: “ Only one general purpose algorithm has been successfully demonstrated on large examples” with reference to GA.

In his dissertation Stehr gives a comprehensive discussion on GA. There are also references to Antreich and Lüder who may have references to us.

To my knowledge, the only biologists that have discussed GA are Brooks and Wiley.

The dissertation of my colleague, Taxén 2003, addresses the problem with information systems used for engineering information management purposes. One detail focuses on the balance between chaos and order in developmental systems. This is also the main concern of the theorem of efficiency in the GA-article. References to GA are made.

Gaines (about learning theory, 1997) has not given any reference to us, but he arrives at the same conclusions as given by our theorem of efficiency – based on information content - from 1991; that it is advisable to be successful in about 100/e = 37% of random trials.

Fisher’s fundamental theorem of natural selection has been discussed by me and others on different forums for instance: http://www.evolutionisdead.com/forum/viewtopic.php?t=330 and http://www.iidb.org/vbb/showthread.php?t=163730&page=5&highlight=rogerg

When it comes to the evolution in the brain, the figure visualises the GA-computation as a matrix multiplication. It fits wery well to the MacLean brain model and that neurons may add, synapses may multiply and axons may delay signal values. That the updating of the moment matrix of the Gaussian in princple follows the well known Hebbian theory of associative learning is perhaps not easily seen by the layman. Every such operation must also be uncertain to some degree and according to Levine, signal values may appear as Gaussian distributed. This is well known from the theory of digital filters and neural networks. Kandel et al. also states that many neurons fire at random. In this sense GA may also contribute to the discussion about free will as an illusion, cp. Zohar 1990.

Even if GA is not discussed and cited very much, it has a wide span over many different fields in optimization , science and philosophy.--Kjells 10:46, 23 April 2007 (UTC)

The well known Finnish brain researcher Matti Bergström developed an entropy model of the brain - based on information theory - already in 1969. A reference to Bergström has now been included. --Kjells 06:23, 29 May 2007 (UTC)

[edit] About the conflict of interest

Some years ago a Swedish biologist told me that Gaussian adaptation (GA) could not contribute anything new to the theory of evolution. The theorem of Fisher (ToF) was sufficient. I recognized that both theorems were about the increase in mean fitness, but also that they told a different story. I expected that ToF should tell the same story as GA in phenotypic space. But there was a difference.

Now, I see no conflict of interest. My interest was to find out why there is a paradox here. I now see why the theorem of Fisher differs from the theorem of Gaussian adaptation (GA), in which only one definition of mean fitness is used. But, in Fisher's theorem two different definitions are used: 1 the mean fitness of offspring (before selection) and 2 the mean fitness of the parents to offspring in the next generation (after selection). Thus far I have always used the same definition of a mathematical entity when trying to investigate its increase (see the definition used in the article). Therefore ToF tells me nothing about the increase in the mean fitness of offspring from one generation to the next (my main concern) or likewise for the parents. The entropy law is ignored and without entropy there will be no evolution. GA will also be unable to work properly without a suitable increase in entropy. I look forward to see a new ToF considering also the entropy law.--Kjells 08:38, 7 August 2007 (UTC) Retrieved from "http://en.wikipedia.org/wiki/Talk:Fisher%27s_fundamental_theorem_of_natural_selection"

[edit] creationists have reason to doubt the classical teory of evolution

A discussion about Fisher's fundamental theorem has recently been held at ScienceBlog, where I have been encouraged to publish some new paper about it. Here is my blog:

Submitted by kjellstrom on Sat, 2008-01-12 03:04. bioscience and medicine

Creationists have reason to doubt the theory based on Fisher’s fundamental theorem of natural selection published in 1930. It relies on the assumption that a gene (allele) may have a fitness of its own being a unit of selection. Historically this way of thinking has also influenced our view of egoism as the most important force in evolution; see for instance Hamilton about kin selection, 1963, or Dawkins about the selfish gene, 1976 in http://en.wikipedia.org/wiki/Gaussian_adaptation#References

On the other hand, if the selection of individuals rules the enrichment of genes, then Gaussian adaptation will perhaps give a more reliable view of evolution (see the blog “Gaussian adaptation as a model of evolution”).

In modern terminology (see Wikipedia) Fisher’s theorem has been stated as: “The rate of increase in the mean fitness of any organism at any time ascribable to natural selection acting through changes in gene frequencies is exactly equal to its genic variance in fitness at that time”. (A.W.F. Edwards, 1994).

A proof as given by Maynard Smith, 1998, shows the theorem to be formally correct. Its formal validity may even be extended to the mean fitness and variance of individual fitness or the fitness of digits in real numbers representing the quantitative traits.

But, if the selection of individuals rules the enrichment of genes, I am afraid there might be a risk that the theory becomes nonsense, and that this is not very well known among biologists.

A drawback is that it does not tell us the increase in mean fitness (see my blog “The definition of fitness of a DNA- or signal message”) from the offspring in one generation to the offspring in the next (which would be expected), but only from offspring to parents in the same generation. Another drawback is that the variance is a genic variance in fitness and not a variance in phenotypes. Therefore, the structure of a phenotypic landscape – which is of considerable importance to a possible increase in mean fitness - can’t be considered. So, it can’t tell us anything about what happens in phenotypic space.

The image shows two different cases (upper and lower) of individual selection, where the green points with fitness = 1 - between the two lines - will be selected, while the red points outside with fitness = 0 will not. The centre of gravity, m, of the offspring is heavy black and ditto of the parents and offspring in the new generation, m* (according to the Hardy-Weinberg law), is heavy red.

http://www.evolution-in-a-nutshell.se/image001.gif

Because the fraction of green feasible points is the same in both cases, Fisher’s theorem states that the increase in mean fitness is equal in both upper and lower case. But the phenotypic variance (not considered by Fisher) in the horizontal direction is larger in the lower case, causing m* to considerably move away from the point of intersection of the lines. Thus, if the lines are pushed towards each other (due to arms races between different species), the risk of getting stuck decreases. This represents a considerable increase in mean fitness (assuming phenotypic variances almost constant). Because this gives room for more phenotypic disorder/entropy/diversity, we may expect diversity to increase according to the entropy law, provided that the mutation is sufficiently high.

So, Fisher’s theorem, the Hardy-Weinberg law or the entropy law does not prove that evolution maximizes mean fitness. On the other hand, Gaussian adaptation obeying the Hardy-Weinberg and entropy laws may perhaps serve as a complement to the classical theory, because it states that evolution may maximize two important collective parameters, namely mean fitness and diversity in parallel (at least with respect to all Gaussian distributed quantitative traits). This may hopefully show that egoism is not the only important force driving evolution, because any trait beneficial to the collective may evolve by natural selection of individuals.

Gkm

http://www.scienceblog.com/cms/creationists-have-reason-doubt-classical-theory-evolution-15214.html

http://www.scienceblog.com/cms/blog/kjellstrom

--Kjells (talk) 07:22, 9 February 2008 (UTC)

[edit] Gaussian adaptation used for other purposes

I have now been able to see that Gaussian adaptation is used for other purposes. One such algorithm is known as the "The Stauffer and Grimson algorithm". See for instance page 2 in

http://lilaproject.org/imatge/_Montse/pub/ICASSP05_xu_landabaso_pardas.pdf

Thus, some text and references has been included in the article. --Kjells (talk) 07:31, 9 February 2008 (UTC)