Gather Adaptive Individuals In Evolving Populations: Models And Algorithms Depicted By Richard K. Belew Shown As Textbook
review I originally published in the Quarterly Biology back in
Like one of Aesops fables, the moral to Adaptive Individuals in Evolving Populations is buried within the book.
In his chapter P. M. Todd observes, “More pernicious to the use of evolutionary simulations in particular is their seductive power to sidetrack scientific inquiry.
It is very appealing and engaging to watch creatures roaming around in a simulated world on ones screen” p.
. Coming from a discipline, psychology, in which pigeons playing “pingpong” was at one time held
to be of profound significance, I would assert that Todds statement could be applied to any overt demonstration of scientific principles.
That is, faced with an increasing number of simulations and complex models, scientists need to acquire the ability to separate pure showmanship and rhetoric from an elucidation of physical reality.
Toward this end, I would recommend Adaptive Individuals in Evolving Populations,
On the surface Adaptive Individuals in Evolving Populations seeks to address the complex relationship between evolution and learning.
Toward this end, the editors organized the book along three categories: Biology, Psychology, and Computer Science, These categories, though, are not defined by the new research they contain but by a highly selective collection of “reprinted classics” that introduces each section.
Hence, Lamarck and Baldwin headline the Biology section William James and Skinner appear among others in the Psychology section and a single “classic” by Hinton and Nolan defines the Computer Science section.
Ignoring the questions of whether these papers are indeed “classics” and whether science, as a discipline has a place for “classics,” the reprinted writings included in the book do make for interesting reading.
I, for one, had never actually read Lamarck, That said, the rhetorical purposes to which these “classics” were put drowns out much of the original research presented in the book.
The “reprinted classics” are used to claim that learning may guide evolution, and that this is a radical concept.
Throughout the book we are told that the “Baldwin effect, . . has not been embraced by biologists as an important force in evolution, to say the least” p.
Further, we are encouraged to vilify the traditionalist mainstream that is not embracing the Baldwin effect, Consider Schulls observation that
William Bateson had popularized Mendels works, coined the term “genetics,” and was such a vigorous antiLamarckian that he probably drove a Lamarckleaning scientific adversary to suicide.
In contradistinction to his father, Gregory Bateson considered Lamarck a greater scientist than Darwin, . . p
One can hardly help but view Gregory as the Luke Skywalker to Williams evil Darth Vader! Gregory Bateson, needless to say, is represented in the “reprinted classics.
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When the contributors to Adaptive Individuals in Evolving Populations cease their rhetorical fingerpointing, much can be learned.
Peter Todd, for instance, presents an intriguing simulation in which learned mate preference affects rates of speciation.
Similarly, Sharoni Shafir and Jonathan Roughgarden present an elegant simulation of memory duration and its potential effect on optimal foraging in the Anolis lizards.
Finally, I was struck by a seeming paradox that emerges when the disparate chapters are taken together.
Namely, since learning may be viewed as “hiding” genetic mutations, it serves to both accelerate and slow down rates of evolution depending on the parameters of a given simulation.
However, none of the papers directly address this paradox,
In summary Adaptive Individuals in Evolving Populations is an exasperating book, The subject it attempts to addressthe impact of learning on evolutionis extremely complex, However, the manner in which the book is presented polarizes more than it elucidates, Much work, both experimental and theoretical, has already addressed the interaction of learning and evolutionary processes, and much remains to be done.
The theory of evolution has been most successful explaining the emergence of new species in terms of their morphological traits.
Ethologists teach that behaviors, too, qualify as firstclass phenotypic features, but evolutionary accounts of behaviors have been much less satisfactory.
In part this is because maturational ”programs” transforming genotype to phenotype are ”open” to environmental influences affected by behaviors.
Further, many organisms are able to continue to modify their behavior, i, e. , learn, even after fully mature, This creates an even more complex relationship between the genotypic features underlying the mechanisms of maturation and learning and the adapted behaviors ultimately selected.
A meeting held at the Santa Fe Institute during the summer ofbrought together a small group of biologists, psychologists, and computer scientists with shared interests in questions such as these.
This volume consists of papers that explore interacting adaptive systems from a range of interdisciplinary perspectives, About half of the articles are classic, seminal references on the subject, ranging from biologists like Lamarck and Waddington to psychologists like Piaget and Skinner.
The other half represent new work by the workshop participants, The role played by mathematical and computational tools, both as models of natural phenomena and as algorithms useful in their own right, is particularly emphasized in these new papers.
In all cases, the prefaces help to put the older papers in a modern context, For the new papers, the prefaces have been written by colleagues from a discipline other than the papers authors, and highlight, for example, what a computer scientist can learn from a biologists model, or vice versa.
Through these crossdisciplinary ”dialogues” and a glossary collecting multidisciplinary connotations of pivotal terms, the process of interdisciplinary investigation itself becomes a central theme.
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