Search results for 'Evolution of Genetic Systems' (try it on Scholar)

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  1. H. G. Hill (1939). The Evolution of Genetic Systems. The Eugenics Review 31 (1):63.
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  2.  3
    Eva Jablonka, Marion J. Lamb & Anna Zeligowski (2006). Evolution in Four Dimensions: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. A Bradford Book.
    Ideas about heredity and evolution are undergoing a revolutionary change. New findings in molecular biology challenge the gene-centered version of Darwinian theory according to which adaptation occurs only through natural selection of chance DNA variations. In Evolution in Four Dimensions, Eva Jablonka and Marion Lamb argue that there is more to heredity than genes. They trace four "dimensions" in evolution -- four inheritance systems that play a role in evolution: genetic, epigenetic, behavioral, and symbolic. (...)
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  3.  34
    Paul E. Griffiths & Russell D. Gray (2004). The Developmental Systems Perspective: Organism-Environment Systems as Units of Development and Evolution. In Massimo Pigliucci & Katherine Preston (eds.), Phenotypic Integration: Studying the Ecology and Evolution of Complex Phenotypes. Oxford University Press 409--431.
    Developmental systems theory is an attempt to sum up the ideas of a research tradition in developmental psychobiology that goes back at least to Daniel Lehrman’s work in the 1950s. It yields a representation of evolution that is quite capable of accommodating the traditional themes of natural selection and also the new results that are emerging from evolutionary developmental biology. But it adds something else - a framework for thinking about development and evolution without the distorting dichotomization (...)
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  4. David Chalmers (1992). The Evolution of Learning: An Experiment in Genetic Connectionism. In Connectionist Models: Proceedings of the 1990 Summer School Workshop. Morgan Kaufmann
    This paper explores how an evolutionary process can produce systems that learn. A general framework for the evolution of learning is outlined, and is applied to the task of evolving mechanisms suitable for supervised learning in single-layer neural networks. Dynamic properties of a network’s information-processing capacity are encoded genetically, and these properties are subjected to selective pressure based on their success in producing adaptive behavior in diverse environments. As a result of selection and genetic recombination, various successful (...)
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  5. Marcello Barbieri (2015). Evolution of the Genetic Code: The Ribosome-Oriented Model. Biological Theory 10 (4):301-310.
    There are currently three major theories on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and the error-minimization theory. The first two assume that the genetic code originated respectively from chemical affinities and from metabolic relationships between codons and amino acids. The error-minimization theory maintains that in primitive systems the apparatus of protein synthesis was extremely prone to errors, and postulates that the genetic code evolved in order to minimize (...)
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  6.  20
    Ehud Lamm (2010). Review Of: Julian Huxley, Evolution: The Modern Synthesis – The Definitive Edition. [REVIEW] Integrative Psychological and Behavioral Science.
    The review focuses on Huxley’s debt to Richard Goldschmidt and Cyril Darlington. I discuss the conceptions of the genome developed by Goldschmidt and Darlington and their continuing relevance.
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  7.  26
    Vincent Bontems (2009). Gilbert Simondon's Genetic “Mecanology”and the Understanding of Laws of Technical Evolution. Techne 13 (1):1-12.
    Since the 1930’s, several attempts have been made to develop a general theory of technical systems or objects and their evolution: in France, Jacques Lafitte, André Leroi-Gourhan, Bertrand Gille, Yves Deforge, and Gilbert Simondon are the main representatives of this trend. In this paper, we focus on the work of Simondon: his analysis of technical progress is based on the hypothesis that technology has its own laws and that customer demand has no paramount influence upon the evolution (...)
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  8.  11
    Isaac Salazar-Ciudad (2013). Evolution in Biological and Non-Biological Systems: The Origins of Life. Biological Theory 7 (1):26-37.
    A replicator is simply something that makes copies of itself. There are hypothetical replicators (e.g., self-catalyzing chemical cycles) that are suspected to be unable to exhibit heritable variation. Variation in any of their constituent molecules would not lead them to produce offspring with those new variant molecules. Copying, such as in DNA replication or in xerox machines, allows any sequence to be remade and then sequence variations to be inherited. This distinction has been used against non-RNA-world hypotheses: without RNA replication (...)
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  9.  73
    Kim Sterelny, Kelly C. Smith & Michael Dickison (1996). The Extended Replicator. Biology and Philosophy 11 (3):377-403.
    This paper evaluates and criticises the developmental systems conception of evolution and develops instead an extension of the gene's eye conception of evolution. We argue (i) Dawkin's attempt to segregate developmental and evolutionary issues about genes is unsatisfactory. On plausible views of development it is arbitrary to single out genes as the units of selection. (ii) The genotype does not carry information about the phenotype in any way that distinguishes the role of the genes in development from (...)
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  10.  7
    Ehud Lamm (2015). Systems Thinking Versus Population Thinking: Genotype Integration and Chromosomal Organization 1930s–1950s. Journal of the History of Biology 1 (4):1-55.
    This article describes how empirical discoveries in the 1930s–1950s regarding population variation for chromosomal inversions affected Theodosius Dobzhansky and Richard Goldschmidt. A significant fraction of the empirical work I discuss was done by Dobzhansky and his coworkers; Goldschmidt was an astute interpreter, with strong and unusual commitments. I argue that both belong to a mechanistic tradition in genetics, concerned with the effects of chromosomal organization and systems on the inheritance patterns of species. Their different trajectories illustrate how scientists’ commitments (...)
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  11.  56
    Nicholas Shea (2012). Genetic Representation Explains the Cluster of Innateness-Related Properties. Mind and Language 27 (4):466-493.
    The concept of innateness is used to make inferences between various better-understood properties, like developmental canalization, evolutionary adaptation, heritability, species-typicality, and so on (‘innateness-related properties’). This article uses a recently-developed account of the representational content carried by inheritance systems like the genome to explain why innateness-related properties cluster together, especially in non-human organisms. Although inferences between innateness-related properties are deductively invalid, and lead to false conclusions in many actual cases, where some aspect of a phenotypic trait develops in reliance (...)
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  12.  5
    Anton V. Sukhoverkhov & Carol A. Fowler (2015). Why Language Evolution Needs Memory: Systems and Ecological Approaches. Biosemiotics 8 (1):47-65.
    The main purpose of this article is to consider the significance of different types of memory and non-genetic inheritance and different biosemiotic systems for the origin and evolution of language. It presents language and memory as distributed, heteronomous and system-determined processes implemented in biological and social domains. The article emphasises that language and other sign systems are both ecological and inductive systems that were caused by and always correlate with the environment and deductive systems (...)
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  13.  58
    Helena Knyazeva (2005). Figures of Time in Evolution of Complex Systems. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 36 (2):289 - 304.
    Owing to intensive development of the theory of self-organization of complex systems called also synergetics, profound changes in our notions of time occur. Whereas at the beginning of the 20th century, natural sciences, by picking up the general spirit of Einstein's theory of relativity, consider a geometrization as an ideal, i.e. try to represent time and force interactions through space and the changes of its properties, nowadays, at the beginning of the 21st century, time turns to be in the (...)
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  14.  18
    Alex Mesoudi, Simon Blanchet, Anne Charmantier, Étienne Danchin, Laurel Fogarty, Eva Jablonka, Kevin N. Laland, Thomas J. H. Morgan, Gerd B. Müller, F. John Odling-Smee & Benoît Pujol (2013). Is Non-Genetic Inheritance Just a Proximate Mechanism? A Corroboration of the Extended Evolutionary Synthesis. Biological Theory 7 (3):189-195.
    What role does non-genetic inheritance play in evolution? In recent work we have independently and collectively argued that the existence and scope of non-genetic inheritance systems, including epigenetic inheritance, niche construction/ecological inheritance, and cultural inheritance—alongside certain other theory revisions—necessitates an extension to the neo-Darwinian Modern Synthesis (MS) in the form of an Extended Evolutionary Synthesis (EES). However, this argument has been challenged on the grounds that non-genetic inheritance systems are exclusively proximate mechanisms that serve (...)
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  15. Helena Knyazeva & Sergei Kurdyumov (2001). Nonlinear Synthesis and Co-Evolution of Complex Systems. World Futures 57 (3):239-261.
    Today a change is imperative in approaching global problems: what is needed is not arm-twisting and power politics, but searching for ways of co-evolution in the complex social and geopolitical systems of the world. The modern theory of self-organization of complex systems provides us with an understanding of the possible forms of coexistence of heterogeneous social and geopolitical structures at different stages of development regarding the different paths of their sustainable co-evolutionary development. The theory argues that the (...)
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  16. R. Brown, J. F. Glazebrook & I. C. Baianu (2007). A Conceptual Construction of Complexity Levels Theory in Spacetime Categorical Ontology: Non-Abelian Algebraic Topology, Many-Valued Logics and Dynamic Systems. [REVIEW] Axiomathes 17 (3-4):409-493.
    A novel conceptual framework is introduced for the Complexity Levels Theory in a Categorical Ontology of Space and Time. This conceptual and formal construction is intended for ontological studies of Emergent Biosystems, Super-complex Dynamics, Evolution and Human Consciousness. A claim is defended concerning the universal representation of an item’s essence in categorical terms. As an essential example, relational structures of living organisms are well represented by applying the important categorical concept of natural transformations to biomolecular reactions and relational structures (...)
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  17. Stan Klein, Leda Cosmides, John Tooby & Sarah Chance (2002). Decisions and the Evolution of Memory: Multiple Systems, Multiple Functions. Psychological Review 109:306-329.
    Memory evolved to supply useful, timely information to the organism’s decision-making systems. Therefore, decision rules, multiple memory systems, and the search engines that link them should have coevolved to mesh in a coadapted, functionally interlocking way. This adaptationist perspective suggested the scope hypothesis: When a generalization is retrieved from semantic memory, episodic memories that are inconsistent with it should be retrieved in tandem to place boundary conditions on the scope of the generalization. Using a priming paradigm and a (...)
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  18.  23
    Ward B. Watt (2013). Causal Mechanisms of Evolution and the Capacity for Niche Construction. Biology and Philosophy 28 (5):757-766.
    Ernst Mayr proposed a distinction between “proximate”, mechanistic, and “ultimate”, evolutionary, causes of biological phenomena. This dichotomy has influenced the thinking of many biologists, but it is increasingly perceived as impeding modern studies of evolutionary processes, including study of “niche construction” in which organisms alter their environments in ways supportive of their evolutionary success. Some still find value for this dichotomy in its separation of answers to “how?” versus “why?”questions about evolution. But “why is A?” questions about evolution (...)
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  19.  84
    Russell Powell & Allen Buchanan (2011). Breaking Evolution's Chains: The Prospect of Deliberate Genetic Modification in Humans. Journal of Medicine and Philosophy 36 (1):6-27.
    Many philosophers invoke the "wisdom of nature" in arguing for varying degrees of caution in the development and use of genetic enhancement technologies. Because they view natural selection as akin to a master engineer that creates functionally and morally optimal design, these authors tend to regard genetic intervention with suspicion. In Part II, we examine and ultimately reject the evolutionary assumptions that underlie the master engineer analogy (MEA). By highlighting the constraints on ordinary unassisted evolution, we show (...)
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  20.  55
    Brian Skyrms, Evolution of Signaling Systems with Multiple Senders and Receivers.
    To coordinate action, information must be transmitted, processed, and utilized to make decisions. Transmission of information requires the existence of a signaling system in which the signals that are exchanged are coordinated with the appropriate content. Signaling systems in nature range from quorum signaling in bacteria [Schauder and Bassler, Kaiser ], through the dance of the bees [Dyer and Seeley ], birdcalls [Hailman, Ficken, and Ficken, Gyger, Marler and Pickert, Evans, Evans, and Marler, Charrier and Sturdy ], and alarm (...)
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  21.  15
    Peter Allen (2000). Knowledge, Ignorance and the Evolution of Complex Systems. World Futures 55 (1):37-70.
    The paper explores the basis for decision?making and policy with regard to the Environment. Clearly these should be based on knowledge of possible consequences and accompanying risk assessments involving the linked behaviour of the many interacting human actors within a socio?economic system and the ecological, and physical systems in which they are embedded. The paper describes the Complex Systems approach to these problems, showing the kind of models that are required in order to obtain whatever limited knowledge is (...)
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  22.  16
    Alexander Laszlo & Kathia Laszlo (2002). The Evolution of Evolutionary Systems Design. World Futures 58 (5 & 6):351 – 363.
    This article presents the genesis of Evolutionary Systems Design (ESD) as a praxis that draws on General Evolution Theory and Social Systems Design methodology, in addition to Critical Systems Theory, to engage in lifelong learning and human development in partnership with the Earth. The contributions of Bela H. Banathy to the creation of ESD are portrayed as bridging evolutionary consciousness and evolutionary action. Following a brief description of the inspiration and mentorship provided by Bela in this (...)
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  23. Patrick Grim, Evolution of Communication with a Spatialized Genetic Algorithm.
    We extend previous work by modeling evolution of communication using a spatialized genetic algorithm which recombines strategies purely locally. Here cellular automata are used as a spatialized environment in which individuals gain points by capturing drifting food items and are 'harmed' if they fail to hide from migrating predators. Our individuals are capable of making one of two arbitrary sounds, heard only locally by their immediate neighbors. They can respond to sounds from their neighbors by opening their mouths (...)
     
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  24.  46
    Patrick Humphreys & Garrick Jones (2006). The Evolution of Group Decision Support Systems to Enable Collaborative Authoring of Outcomes. World Futures 62 (3):193 – 222.
    This article draws on analysis of a variety of problems emerging from practical applications of Group Decision Support Systems (GDSS) to propose a fundamental evolution of decision support models from the traditional single decision-spine model to the decision-hedgehog. It positions decision making through the construction of narratives making the rhizome that constitutes the body of the hedgehog with the fundamental aim of enriching understanding of the contexts of decision making. Localized processes constructing and exploring prescriptions for action within (...)
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  25.  30
    James Griesemer, Matthew H. Haber, Grant Yamashita & Lisa Gannett (2005). Critical Notice: Cycles of Contingency – Developmental Systems and Evolution. [REVIEW] Biology and Philosophy 20 (2-3):517-544.
    The themes, problems and challenges of developmental systems theory as described in Cycles of Contingency are discussed. We argue in favor of a robust approach to philosophical and scientific problems of extended heredity and the integration of behavior, development, inheritance, and evolution. Problems with Sterelny's proposal to evaluate inheritance systems using his `Hoyle criteria' are discussed and critically evaluated. Additional support for a developmental systems perspective is sought in evolutionary studies of performance and behavior modulation of (...)
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  26.  21
    L. Dennis, R. W. Gray, L. H. Kauffman, J. Brender McNair & N. J. Woolf (2009). A Framework Linking Non-Living and Living Systems: Classification of Persistence, Survival and Evolution Transitions. [REVIEW] Foundations of Science 14 (3):217-238.
    We propose a framework for analyzing the development, operation and failure to survive of all things, living, non-living or organized groupings. This framework is a sequence of developments that improve survival capability. Framework processes range from origination of any entity/system, to the development of increased survival capability and development of life-forms and organizations that use intelligence. This work deals with a series of developmental changes that arise from the uncovering of emergent properties. The framework is intended to be general, but (...)
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  27.  17
    Lakshmi J. Gogate (2006). Dynamic Systems and the Evolution of Language. Behavioral and Brain Sciences 29 (3):286-287.
    Locke & Bogin (L&B) suggest that theoretical principles of ontogenetic development apply to language evolution. If this is the case, then evolutionary theory should utilize epigenetic theories of development to theorize, model, and elucidate the evolution of language wherever possible. In this commentary, I evoke principles of dynamic systems theory to evaluate the evolutionary phenomena presented in the target article.
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  28.  11
    Allan Combs & Sally Goerner (1997). The Evolution of Consciousness as a Self-Organizing Information System in the Society of Other Such Systems. World Futures 50 (1):609-616.
    (1997). The evolution of consciousness as a self‐organizing information system in the society of other such systems. World Futures: Vol. 50, No. 1-4, pp. 609-616.
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  29.  8
    Mika Pantzar (1993). Editorial Introduction to Special Issue on Evolution of Socio-Economic Systems. World Futures 37 (2):1-3.
    (1993). Editorial introduction to special issue on evolution of socio‐economic systems. World Futures: Vol. 37, The Evolution of Socio-Economic Systems, pp. 1-3.
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  30. Kai Hahlweg (1983). The Evolution of Science: A Systems Approach. Dissertation, The University of Western Ontario (Canada)
    This thesis is concerned with two interrelated sets of problems: How can we have knowledge in a universe of processes? How can knowledge be improved, and how is scientific progress possible? ;To address the epistemological question in conjunction with the ontological is not a common approach in contemporary philosophy of science. I therefore begin the dissertation by arguing that these two areas of philosophy are intimately interrelated, and that the one-sided concentration on epistemological issues has led to an unsatisfactory account (...)
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  31.  8
    Deena Emera, Roberto Romero & Günter Wagner (2012). The Evolution of Menstruation: A New Model for Genetic Assimilation. Bioessays 34 (1):26-35.
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  32.  4
    Kepa Ruiz-Mirazo & Alvaro Moreno (2013). Synthetic Biology: Challenging Life in Order to Grasp, Use, or Extend It. Biological Theory 8 (4):376-382.
    In this short contribution we explore the historical roots of recent synthetic approaches in biology and try to assess their real potential, as well as identify future hurdles or the reasons behind some of the main difficulties they currently face. We suggest that part of these difficulties might not be just the result of our present lack of adequate technical skills or understanding, but could spring directly from the nature of the biological phenomenon itself. In particular, if life is conceived (...)
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  33.  7
    Chris Salzberg & Hiroki Sayama (2004). Complex Genetic Evolution of Artificial Self-Replicators in Cellular Automata. Complexity 10 (2):33-39.
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  34.  1
    Alexei A. Sharov (2009). Role of Utility and Inference in the Evolution of Functional Information. Biosemiotics 2 (1):101-115.
    Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility (...)
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  35.  3
    Robert Zimmer, Robert Holte & Alan MacDonald (1997). The Impact of Representation on the Efficacy of Artificial Intelligence: The Case of Genetic Algorithms. [REVIEW] AI and Society 11 (1-2):76-87.
    This paper is about representations for Artificial Intelligence systems. All of the results described in it involve engineering the representation to make AI systems more effective. The main AI techniques studied here are varieties of search: path-finding in graphs, and probablilistic searching via simulated annealing and genetic algorithms. The main results are empirical findings about the granularity of representation in implementations of genetic algorithms. We conclude by proposing a new algorithm, called “Long-Term Evolution,” which is (...)
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  36.  2
    Arthur M. Silverstein (2015). Promethean Evolution: A Comparison of the Immune and Neural Systems. Perspectives in Biology and Medicine 57 (4):449-469.
    …behind the diversity of discoveries [in molecular biology] moved a unity, a constant direction of change, the development of the concept of biological specificity.In his landmark book Evolution by Gene Duplication, geneticist Susumu Ohno pointed out that whereas most evolutionary developments represent adjustments to past challenges and mutations, two unique systems had evolved to deal with future challenges: the immune response and neural memory functions. He named these two evolutionary modes after the Titan brothers of Greek mythology: “standard” (...)
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  37.  22
    Mark A. Bedau, Optimal Formulation of Complex Chemical Systems with a Genetic Algorithm.
    We demonstrate a method for optimizing desired functionality in real complex chemical systems, using a genetic algorithm. The chemical systems studied here are mixtures of amphiphiles, which spontaneously exhibit a complex variety of self-assembled molecular aggregations, and the property optimized is turbidity. We also experimentally resolve the fitness landscape in some hyper-planes through the space of possible amphiphile formulations, in order to assess the practicality of our optimization method. Our method shows clear and significant progress after testing (...)
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  38.  9
    Herbert F. Mataré (1999). Bioethics: The Ethics of Evolution and Genetic Interference. Bergin & Garvey.
    From a scientific approach, this work explores the moral implications of genetic engineering and argues for corrective genetic interference.
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  39.  2
    Jean-Pierre Aubin (2003). Adaptive Evolution of Complex Systems Under Uncertain Environmental Constraints: A Viability Approach. In J. B. Nation (ed.), Formal Descriptions of Developing Systems. Kluwer Academic Publishers 165--184.
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  40.  67
    Tom Wenseleers & Annette Van Oystaeyen (2011). Unusual Modes of Reproduction in Social Insects: Shedding Light on the Evolutionary Paradox of Sex. Bioessays 33 (12):927-937.
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  41.  2
    Carmel M. Martin & Margot Félix‐Bortolotti (2010). W(H)Ither Complexity? The Emperor's New Toolkit? Or Elucidating the Evolution of Health Systems Knowledge? Journal of Evaluation in Clinical Practice 16 (3):415-420.
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  42.  9
    Hannah Rubin (2015). Genetic Models in Evolutionary Game Theory: The Evolution of Altruism. Erkenntnis 80 (6):1175-1189.
    While prior models of the evolution of altruism have assumed that organisms reproduce asexually, this paper presents a model of the evolution of altruism for sexually reproducing organisms using Hardy–Weinberg dynamics. In this model, the presence of reciprocal altruists allows the population to evolve to a stable polymorphic population where the majority of organisms are altruistic. Further, adding stochasticity leads to even larger numbers of altruists, while adding stochasticity to an analogous asexual model leads to more selfish organisms. (...)
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  43.  13
    I. Walker & R. M. Williams (1976). The Evolution of the Cooperative Group. Acta Biotheoretica 25 (1):1-43.
    A simple model, illustrating the transition from a population of free swimming, solitary cells to one consisting of small colonies serves as a basis to discuss the evolution of the cooperative group. The transition is the result of a mutation of the dynamics of cell division, delayed cell separation leads to colonies of four cells. With this mutation cooperative features appear, such as synchronised cell divisions within colonies and coordinated flagellar function which enables the colony to swim in definite (...)
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  44.  10
    Robert B. Eckhardt (2006). The Evolution of Language: Present Behavioral Evidence for Past Genetic Reprogramming in the Human Lineage. Behavioral and Brain Sciences 29 (3):284-285.
    Language and life history can be related functionally through the study of human ontogeny, thus usefully informing our understanding of several unique aspects of the evolution of species. The operational principles outlined by Locke & Bogin (L&B) demonstrate that the present can provide a useful framework for understanding the past.
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  45.  3
    R. M. Williams & I. Walker (1978). The Evolution of Sexual Reproduction as a Repair Mechanism Part II. Mathematical Treatment of the Wheel Model and its Significance for Real Systems. Acta Biotheoretica 27 (3-4):159-184.
    The dynamics of populations of self-replicating, hierarchically structured individuals, exposedto accidents which destroy their sub-units, is analyzed mathematically, specifically with regardto the roles of redundancy and sexual repair. The following points emerge from this analysis:0 A population of individuals with redundant sub-structure has no intrinsic steady-statepoint; it tends to either zero or infinity depending on a critical accident rate α c . Increased redundancy renders populations less accident prone initially, but populationdecline is steeper if a is greater than a fixed (...)
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  46.  11
    Nicolas Fay, Simon Garrod, Leo Roberts & Nik Swoboda (2010). The Interactive Evolution of Human Communication Systems. Cognitive Science 34 (3):351-386.
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  47.  14
    Tadeusz Wieslaw Zawidzki (1998). Competing Models of Stability in Complex, Evolving Systems: Kauffman Vs. Simon. [REVIEW] Biology and Philosophy 13 (4):541-554.
    I criticize Herbert Simon 's argument for the claim that complex natural systems must constitute decomposable, mereological or functional hierarchies. The argument depends on certain assumptions about the requirements for the successful evolution of complex systems, most importantly, the existence of stable, intermediate stages in evolution. Simon offers an abstract model of any process that succeeds in meeting these requirements. This model necessarily involves construction through a decomposable hierarchy, and thus suggests that any complex, natural, i.e., (...)
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  48.  11
    I. Walker (1996). Prediction of Evolution? Somatic Plasticity as a Basic, Physiological Condition for the Viability of Genetic Mutations. Acta Biotheoretica 44 (2):165-168.
    The argument is put forward that genetic mutations are viable then only, when the changed pattern of growth and/or metabolism is accommodated by the taxon-specific biochemistry of the organisms, i.e. by adaptive, somatic/physiological plasticity. The range of somatic plasticity under changing environmental conditions, therefore, has a certain predictive value for the kind of mutations that are likely to be viable.
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  49. James Mark Baldwin (1902/2005). Development and Evolution: Including Psychophysical Evolution, Evolution by Orthoplasy, and the Theory of Genetic Modes. Blackburn Press.
  50.  13
    Ping Ao, Chulan Kwon & Hong Qian (2007). On the Existence of Potential Landscape in the Evolution of Complex Systems. Complexity 12 (4):19-27.
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