Revisiting Hull's Evolutionary Model of Science

2021 ◽  
Vol 13 (2) ◽  
pp. 145-152
Author(s):  
Mohammad Mahdi Hatef ◽  
Keyword(s):  
Natural Selection ◽  
Selection Process ◽  
Biological Evolution ◽  
Evolutionary Model ◽  
Scientific Change ◽  
Evolutionary Models ◽  
Natural Evolution ◽  
The Difference

Evolutionary models for scientific change are generally based on an analogy between scientific changes and biological evolution. Some dissimilarity cases, however, challenge this analogy. An issue discussed in this essay is that despite natural evolution, which is currently considered to be non-globally progressive, science is a phenomenon that we understand as globally progressive. David Hull's solution to this disanalogy is to trace the difference back to their environments, in which processes of natural selection and conceptual selection occur. I will provide two arguments against this solution, showing that Hull's formulation of natural selection prohibits him from removing the environment from the selection process. Then I point to a related tension in his theory, between realism and externalism in science, and give some suggestions to solve these tensions.

Modeling Spatial Phenomena

2001 ◽  
Author(s):  
Roman M. Krzanowski ◽  
Jonathan Raper
Keyword(s):  
Evolutionary Algorithms ◽  
Spatial Modeling ◽  
General Framework ◽  
Evolutionary Model ◽  
Spatial Modelling ◽  
Evolutionary Models ◽  
Evolutionary Modeling ◽  
Specific Data ◽  
Distinct Class ◽  
The Difference

In part II we describe some possible methods of modeling spatial phenomena with spatial evolutionary algorithms. We will explain what spatial evolutionary models and spatial evolutionary algorithms are and how they can be designed. We will also provide a general framework for spatial evolutionary modeling. We believe that this framework can be used to create evolutionary models (and algorithms) of spatial phenomena that will reach well beyond the model discussed in the book. Wherever possible we will give examples to illustrate the concepts, terms, and procedures we discuss. In fact, by the end of part II we will have built, using presented principles, a complete spatial evolutionary model—a spatial evolutionary model of a wireless communication system. We shall begin our discussion with an explanation of the distinction between spatial evolutionary models and evolutionary models of spatial phenomena. As we shall see, the difference between these two terms, while subtle, is very important for the understanding of spatial modeling in general and evolutionary spatial modeling in particular. . . . "Spatial Evolutionary Models" Versus "Evolutionary Models of Spatial Phenomena" . . . The differences between the terms spatial evolutionary models and evolutionary models of spatial phenomena extend well beyond their lexical dissimilarities and touch upon very basic issues of evolutionary and spatial modeling. The term spatial evolutionary model, as used here, refers to an evolutionary model that constitutes a separate, distinct class of computer evolutionary models. In contrast, the term evolutionary models of spatial phenomena denotes applications of existing evolutionary methods (or mere extensions of established evolutionary methodologies) to problems defined in space. Our view of the science of spatial modelling is driven by the choice of which definition, along with its consequences, that we accept. If we accept that spatial evolutionary models constitute a separate and distinct class of evolutionary models, then we will also have to accept the proposition that they possess unique rules governing their behavior, a unique genome design to represent a model-specific data structure, and a set of unique operators that cannot be readily applied to nonspatial problems. Moreover, it will follow that these evolutionary models also possess problem-specific language, that is language specific to the domain of spatial evolutionary models.

scholarly journals La evolución de técnicas y fenómenos: hacia una explicación de la "confección" del mundo

1996 ◽  
Vol 28 (82) ◽  
pp. 25-66
Author(s):  
Sergio F. Martínez ◽  
Edna Suárez
Keyword(s):  
Population Biology ◽  
Evolutionary Process ◽  
Evolutionary Model ◽  
Nucleic Acid Hybridization ◽  
Experimental Techniques ◽  
Scientific Change ◽  
Causal Process ◽  
Evolutionary Models ◽  
The World ◽  
Common Objection

In recent articles some authors (e.g. Pickering 1989, Hacking 1992) have pointed out a process of gradual adjustment or tailoring between phenomena, models and experimental techniques. However, the whole idea of tailoring or adjusting has been dealt with as a mere metaphore. In this paper we present an evolutionary model of phenomena and techniques which explains this gradual adjustment or tailoring as an adaptative causal process, i.e. not as a mere metaphor. Our aim is accomplished in three steps. First, we arrive at the general conditions that changes in a population of entities with reproductive capabilities have to satisfy in order to be modelled as an evolutionary process, in a causal-explanatory sense. We show that a characterization of the class of experimental techniques (a class associated with an experimental tradition) meet these conditions, and we examine in detail how the nucleic acid hybridization techniques used in molecular biology can be modelled in the way we propose. A second step is to show that the sort of variability that metters in evolutionary models of techniques and phenomena is aggregative variability, i.e. the sort of variability that can be selected. This is an important point, since most evolutionary models of technical and scientific change in the literature fail to satisfy this requirement. A common objection to evolutionary models of scientific change is that fitness, the central notion of evolutionary models in population biology, has no counterpart in these models. We show that our model can provide a natural concept of fitness, a concept that has a similar role to play in our model as in biological models. Finally, as a third step, we conclude with an explanation of how the world can be said to be tailored. It is the result of an evolutionary process which incorporates inextricably related conceptual and material resources. In this sense, the world consists of phenomena that are made by us, but which are not mere inventions of our mind.

Randomness and Complexity

2018 ◽  
Author(s):  
Steven E. Vigdor
Keyword(s):  
Quantum Mechanics ◽  
Natural Selection ◽  
Rna World ◽  
Biological Evolution ◽  
Variable Theory ◽  
Cosmological Natural Selection ◽  
Einstein Podolsky Rosen ◽  
World Hypothesis ◽  
Rna World Hypothesis

Chapter 7 describes the fundamental role of randomness in quantum mechanics, in generating the first biomolecules, and in biological evolution. Experiments testing the Einstein–Podolsky–Rosen paradox have demonstrated, via Bell’s inequalities, that no local hidden variable theory can provide a viable alternative to quantum mechanics, with its fundamental randomness built in. Randomness presumably plays an equally important role in the chemical assembly of a wide array of polymer molecules to be sampled for their ability to store genetic information and self-replicate, fueling the sort of abiogenesis assumed in the RNA world hypothesis of life’s beginnings. Evidence for random mutations in biological evolution, microevolution of both bacteria and antibodies and macroevolution of the species, is briefly reviewed. The importance of natural selection in guiding the adaptation of species to changing environments is emphasized. A speculative role of cosmological natural selection for black-hole fecundity in the evolution of universes is discussed.

scholarly journals How culture and biology interact to shape language and the language faculty

2018 ◽  
Author(s):  
Kenny Smith
Keyword(s):  
Language Learning ◽  
Cultural Evolution ◽  
Cognitive Biases ◽  
Biological Evolution ◽  
Evolutionary Process ◽  
Evolutionary Models ◽  
Language Faculty ◽  
Repeated Cycle ◽  
Individual Level ◽  
Precise Relationship

Recent work suggests that linguistic structure develops through cultural evolution, as a consequence of the repeated cycle of learning and use by which languages persist. This work has important implications for our understanding of the evolution of the cognitive basis for language: in particular, human language and the cognitive capacities underpinning it are likely to have been shaped by co-evolutionary processes, where the cultural evolution of linguistic systems is shaped by and in turn shapes the biological evolution of the capacities underpinning language learning. I review several models of this co-evolutionary process, which suggest that the precise relationship between evolved biases in individuals and the structure of linguistic systems depends on the extent to which cultural evolution masks or unmasks individual-level cognitive biases from selection. I finish by discussing how these co-evolutionary models might be extended to cases where the biases involved in learning are themselves shaped by experience, as is the case for language.

scholarly journals The Impact of 'Anthropotechnology' on Human Evolution

2010 ◽  
Vol 14 (2) ◽  
pp. 72-87 ◽  
Author(s):  
Sylvia Blad ◽  
Keyword(s):  
Natural Selection ◽  
Human Evolution ◽  
Common Ancestor ◽  
Biological Evolution ◽  
Genetic Effects ◽  
Evolutionary Path ◽  
Peter Sloterdijk ◽  
The Impact

From the time that they diverged from their common ancestor, chimpanzees and humans have had a very different evolutionary path. It seems obvious that the appearance of culture and technology has increasingly alienated humans from the path of natural selection that has informed chimpanzee evolution. According to philosopher Peter Sloterdijk any type of technology is bound to have genetic effects. But to what extent do genomic comparisons provide evidence for such an impact of ‘anthropotechnology’ on our biological evolution?

The naked ape as an evolutionary model, 50 years later

2018 ◽  
Vol 68 (3) ◽  
pp. 227-246
Author(s):  
Nico M. van Straalen
Keyword(s):  
Natural Selection ◽  
Evolutionary Biology ◽  
Evolutionary Model ◽  
Developmental Constraints ◽  
Body Hair ◽  
Product Evolution ◽  
Adaptive Explanation ◽  
History Of ◽  
Popular Texts ◽  
The Brain

AbstractEvolution acts through a combination of four different drivers: (1) mutation, (2) selection, (3) genetic drift, and (4) developmental constraints. There is a tendency among some biologists to frame evolution as the sole result of natural selection, and this tendency is reinforced by many popular texts. “The Naked Ape” by Desmond Morris, published 50 years ago, is no exception. In this paper I argue that evolutionary biology is much richer than natural selection alone. I illustrate this by reconstructing the evolutionary history of five different organs of the human body: foot, pelvis, scrotum, hand and brain. Factors like developmental tinkering, by-product evolution, exaptation and heterochrony are powerful forces for body-plan innovations and the appearance of such innovations in human ancestors does not always require an adaptive explanation. While Morris explained the lack of body hair in the human species by sexual selection, I argue that molecular tinkering of regulatory genes expressed in the brain, followed by positive selection for neotenic features, may have been the driving factor, with loss of body hair as a secondary consequence.

Combinatorics of Genotype-Phenotype Maps: An RNA Case Study

2005 ◽  
Author(s):  
Christian M. Reidys
Keyword(s):  
Natural Selection ◽  
Genetic Drift ◽  
Optimization Problem ◽  
Neutral Theory ◽  
Biological Evolution ◽  
Neutral Evolution ◽  
Evolutionary Search ◽  
Random Drift ◽  
Molecular Change ◽  
Biological Phenomena

The fundamental mechanisms of biological evolution have fascinated generations of researchers and remain popular to this day. The formulation of such a theory goes back to Darwin (1859), who in the The Origin of Species presented two fundamental principles: genetic variability caused by mutation, and natural selection. The first principle leads to diversity and the second one to the concept of survival of the fittest, where fitness is an inherited characteristic property of an individual and can basically be identified with its reproduction rate. Wright [530, 531] first recognized the importance of genetic drift in evolution in improving the evolutionary search capacity of the whole population. He viewed genetic drift merely as a process that could improve evolutionary search. About a decade later, Kimura proposed [317] that the majority of changes that are observed in evolution at the molecular level are the results of random drift of genotypes. The neutral theory of Kimura does not deny that selection plays a role, but claims that no appreciable fraction of observable molecular change can be caused by selective forces: mutations are either a disadvantage or, at best, neutral in present day organisms. Only negative selection plays a major role in the neutral evolution, in that deleterious mutants die out due to their lower fitness. Over the last few decades, there has been a shift of emphasis in the study of evolution. Instead of focusing on the differences in the selective value of mutants and on population genetics, interest has moved to evolution through natural selection as an abstract optimization problem. Given the tremendous opportunities that computer science and the physical sciences now have for contributing to the study of biological phenomena, it is fitting to study the evolutionary optimization problem in the present volume. In this chapter, we adopt the following framework: assuming that selection acts exclusively upon isolated phenotypes, we introduce the following compositum of mappings . . . Genotypes→ Phenotypes →Fitness . . . . We will refer to the first map as to the genotype-phenotype map and call the preimage of a given phenotype its neutral network. Clearly, the main ingredients here are the phenotypes and genotypes and their respective organization. In the following we will study various combinatorial properties of phenotypes and genotypes for RNA folding maps.

Adaptation and Natural Selection

2021 ◽  
pp. 125-154
Author(s):  
Áki J. Láruson ◽  
Floyd A. Reed
Keyword(s):  
Natural Selection ◽  
Allele Frequency ◽  
Levels Of Selection ◽  
Frequency Data ◽  
Selection Coefficient ◽  
Frequency Distributions ◽  
Single Allele ◽  
Selection Strength ◽  
The Difference ◽  
Over Time

Here non-random shifts in allele frequencies over time are introduced, as well as how to incorporate varying levels of selection into a model of a single population through time. This chapter highlights the difference between weak and strong selection, the dynamics of single allele versus genotype-level selection, and how selection strength and population size affect allele frequency distributions over time. Finally the inference of the selection coefficient from allele frequency data is discussed, alongside the concepts of overdominance and underdominance.

On the Adaptive Cycle of Transformational Change: A Proposal for a Panarchical Expansion of Escalation Theory

2008 ◽  
Vol 14 ◽  
pp. 335-355
Author(s):  
Gregory P. Dietl
Keyword(s):  
Explanatory Power ◽  
Biological Evolution ◽  
Transformational Change ◽  
Robert Frost ◽  
Systems Ecology ◽  
Adaptive Cycle ◽  
Nested Sets ◽  
The Difference ◽  
The One ◽  
Ecologically Sustainable

An outstanding challenge with broad implications for an ecologically sustainable future is to understand how living systems—whether natural or social—balance opportunity and constraint in a given environment. In this paper, I compare the proposed mechanics of a heuristic developed to explain transformational change in systems ecology with various paleontological patterns and hypotheses for its conceptual homology and thus explanatory power in causal terms. The adaptive cycle heuristic, which has potential to influence current environmental and natural resources law and policy, has two components: 1) cycles that alternate between long periods of growth and shorter periods that create opportunities for innovation (new structures or conditions that become economically successful), and 2) the interaction of nested sets of such cycles (panarchies) across space and time scales. I critically evaluate three basic underlying tenets of the adaptive cycle related to the circumstances of innovation—empty niche space, competition and availability of resources—because of their importance to the development of a theoretical framework for understanding the ecological dimension of opportunity in biological evolution. I conclude that not all of the proposed mechanics and observed phenomenology of the adaptive cycle are appropriate in biological evolution. I draw insight, however, from the hierarchical nature of the heuristic to outline a “panarchical” conceptualization of the escalation hypothesis; I identify self-organization, emergence, selection and adaptation, and feedback as phenomena that are held in common across systems and scales, which influence how entities in the economic hierarchy of life arise, interact and evolve.Two roads diverged in a wood, and I, I took the one less traveled by, and that has made all the difference.Robert Frost.Every system either finds a way to develop or else collapses.Aleksander Solzhenitsyn

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