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What ls Life

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  1. What is Life?Guenther Witzany - 2020 - Frontiers in Astronomy and Space Sciences 7:1-13.
    In searching for life in extraterrestrial space, it is essential to act based on an unequivocal definition of life. In the twentieth century, life was defined as cells that self-replicate, metabolize, and are open for mutations, without which genetic information would remain unchangeable, and evolution would be impossible. Current definitions of life derive from statistical mechanics, physics, and chemistry of the twentieth century in which life is considered to function machine like, ignoring a central role of communication. Recent observations show (...)
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  • Vaulting optimality.Peter Dayan & Jon Oberlander - 1991 - Behavioral and Brain Sciences 14 (2):221-222.
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  • Organisms, scientists and optimality.Michael Davison - 1991 - Behavioral and Brain Sciences 14 (2):220-221.
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  • Natural selection doesn't have goals, but it's the reason organisms do.Martin Daly - 1991 - Behavioral and Brain Sciences 14 (2):219-220.
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  • Some optimality principles in evolution.James F. Crow - 1991 - Behavioral and Brain Sciences 14 (2):218-219.
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  • Complexity: An energetics agenda.Eric J. Chaisson - 2004 - Complexity 9 (3):14-21.
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  • Criteria for optimality.Michel Cabanac - 1991 - Behavioral and Brain Sciences 14 (2):218-218.
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  • The quest for plausibility: A negative heuristic for science?R. W. Byrne - 1991 - Behavioral and Brain Sciences 14 (2):217-218.
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  • Resourceful Event-Predictive Inference: The Nature of Cognitive Effort.Martin V. Butz - 2022 - Frontiers in Psychology 13.
    Pursuing a precise, focused train of thought requires cognitive effort. Even more effort is necessary when more alternatives need to be considered or when the imagined situation becomes more complex. Cognitive resources available to us limit the cognitive effort we can spend. In line with previous work, an information-theoretic, Bayesian brain approach to cognitive effort is pursued: to solve tasks in our environment, our brain needs to invest information, that is, negative entropy, to impose structure, or focus, away from a (...)
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  • On "huxleys evolution and ethics in sociobiological perspective" by George C. Williams.Ralph Wendell Burhoe - 1988 - Zygon 23 (4):417-430.
    I concur with Williams that improving human ethics requires full consideration of the biogenetic facts; but I argue that the understanding of biogenetic facts, and of ethics also, can be improved by a fuller view of nature's mechanism for selecting what is fit, a view recently generated by physical scientists. For me ethics necessarily must fit the evolved genotype, but ethics does not emerge until the rise of cultural evolution, where nature selects a culturetype symbiotic with the genotype. I outline (...)
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  • Optimality as a mathematical rhetoric for zeroes.Fred L. Bookstein - 1991 - Behavioral and Brain Sciences 14 (2):216-217.
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  • Optimality as an evaluative standard in the study of decision-making.Jonathan Baron - 1991 - Behavioral and Brain Sciences 14 (2):216-216.
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  • Scientific revolution and the evolution of consciousness.Robert Artigiani - 1988 - World Futures 25 (3):237-281.
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  • Optimality and human memory.John R. Anderson - 1991 - Behavioral and Brain Sciences 14 (2):215-216.
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  • ASPECTOS HUMANÍSTICOS DE LA ECOLOGÍA.Miguel Acosta, Pablo Martínez de Anguita & Mª Angeles Martín (eds.) - 2006 - Madrid, España: Publicep.
    Estamos siendo testigos de grandes avances tecnológicos y, a la vez, de grandes desastres naturales y sociales que nos impulsan a plantearnos cuáles son las causas últimas de la degradación natural ecológica. El abuso en el uso de los recursos tal vez pueda tener relación con el abuso en el uso de la tecnología; incluso ser causa de la gran desigualdad social en el acceso a bienes necesarios para llevar una vida digna, raíz de muchos conflictos sociales. La ecología es (...)
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  • The animal as a pluricausal system.H. P. Wolvekamp - 1982 - Acta Biotheoretica 31 (1):29-43.
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  • Is economics still immersed in the old concepts of the Enlightenment era?Andrzej P. Wierzbicki - 1991 - Behavioral and Brain Sciences 14 (2):236-237.
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  • Entropy and information: Suggestions for common language.Jeffrey S. Wicken - 1987 - Philosophy of Science 54 (2):176-193.
    Entropy and information are both emerging as currencies of interdisciplinary dialogue, most recently in evolutionary theory. If this dialogue is to be fruitful, there must be general agreement about the meaning of these terms. That this is not presently the case owes principally to the supposition of many information theorists that information theory has succeeded in generalizing the entropy concept. The present paper will consider the merits of the generalization thesis, and make some suggestions for restricting both entropy and information (...)
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  • The engagement of religion and biology: A case study in the mediating role of metaphor in the sociobiology of Lumsden & Wilson. [REVIEW]Jitse M. van der Meer - 2000 - Biology and Philosophy 15 (5):669-698.
    I claim that explanations of human behaviour by Edward O. Wilsonand Charles Lumsden are constituted by a religiously functioningmetaphysics: emergent materialism. The constitutive effects areidentified using six criteria, beginning with a metaphorical re-description of dissimilarities between levels of organization interms of the lower level, and consist of conceptual andexplanatory reductions (CER). Wilson and Lumsden practice CER,even though CER is not required by emergent materialism. Theypreconceive this practice by a re-description which conflates thelevels of organization and explain failure of CER in (...)
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  • On the light doves and learning on mistakes.Vuk Uskoković - 2009 - Axiomathes 19 (1):17-50.
    Each type of learning is proposed as being a three-stage process, composed of: (i) recognition of a perceptual situation and performance of an action corresponding thereto; (ii) observation of a deviation of the action result from an expected outcome; (iii) re-arrangement of the conceptual framework of reasoning to meaningfully assimilate the observed deviation. In order to evaluate a general, systemic significance of the concept of learning proposed hereby, the latter is assessed from perspectives that correspond to diverse levels of organizational (...)
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  • The human being as a bumbling optimalist: A psychologist's viewpoint.Masanao Toda - 1991 - Behavioral and Brain Sciences 14 (2):235-235.
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  • Optimal confusion.Stephanie Stolarz-Fantino & Edmund Fantino - 1991 - Behavioral and Brain Sciences 14 (2):234-234.
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  • Avoid the push-pull dilemma in explanation.Kenneth M. Steele - 1991 - Behavioral and Brain Sciences 14 (2):233-234.
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  • Extremum descriptions, process laws and minimality heuristics.Elliott Sober - 1991 - Behavioral and Brain Sciences 14 (2):232-233.
    The examples and concepts that Shoemaker cites are rather heterogeneous. Some distinctions need to be drawn. An optimality thesis involves not just an ordering of options, but a value judgment about them. So let us begin by distinguishing minimality from optimality. And the concept of minimality can play a variety of roles, among which I distinguish between extremum descriptions, statements hypothesizing an optimizing process, and methodological recommendations. Finally, I consider how the three categories relate to Shoemaker’s question that “Who is (...)
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  • Rational agents, real people and the quest for optimality.Eldar Shafir - 1991 - Behavioral and Brain Sciences 14 (2):232-232.
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  • The strategy of optimality revisited.Paul J. H. Schoemaker - 1991 - Behavioral and Brain Sciences 14 (2):237-245.
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  • The quest for optimality: A positive heuristic of science?Paul J. H. Schoemaker - 1991 - Behavioral and Brain Sciences 14 (2):205-215.
    This paper examines the strengths and weaknesses of one of science's most pervasive and flexible metaprinciples;optimalityis used to explain utility maximization in economics, least effort principles in physics, entropy in chemistry, and survival of the fittest in biology. Fermat's principle of least time involves both teleological and causal considerations, two distinct modes of explanation resting on poorly understood psychological primitives. The rationality heuristic in economics provides an example from social science of the potential biases arising from the extreme flexibility of (...)
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  • The autogenesis of the self.Michael L. Schwalbe - 1991 - Journal for the Theory of Social Behaviour 21 (3):269–295.
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  • Should the quest for optimality worry us?Nils-Eric Sahlin - 1991 - Behavioral and Brain Sciences 14 (2):231-231.
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  • Entropy and evil.Robert John Russell - 1984 - Zygon 19 (4):449-468.
    This paper explores a possible relationship between entropy and evil in terms of metaphor. After presenting the various meanings of entropy in classical thermodynamics and statical mechanics, and the Augustinian and Irenaean theodicies, several similarities and dissimilarities between entropy and evil are described. Underlying the concepts of evil and entropy is the assumption that time has a direction. After examining the scientific basis for this assumption, it is hypothesized that, if evil is real in nature, entropy is what one would (...)
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  • Optimality as a prescriptive tool.Alexander H. G. Rinnooy Kan - 1991 - Behavioral and Brain Sciences 14 (2):230-231.
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  • Locality, Bell's theorem, and quantum mechanics.Peter Rastall - 1985 - Foundations of Physics 15 (9):963-972.
    Classical relativistic physics assumes that spatially separated events cannot influence one another (“locality”) and that values may be assigned to quantities independently of whether or not they are actually measured (“realism”). These assumptions have consequences—the Bell inequalities—that are sometimes in disagreement with experiment and with the predictions of quantum mechanics. It has been argued that, even if realism is not assumed, the violation of the Bell inequalities implies nonlocality—and hence that radical changes are necessary in the foundations of physics. We (...)
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  • Don't just sit there, optimise something.J. H. P. Paelinck - 1991 - Behavioral and Brain Sciences 14 (2):230-230.
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  • Proteins, the chaperone function and heredity.Valeria Mosini - 2013 - Biology and Philosophy 28 (1):53-74.
    In this paper I use a case study—the discovery of the chaperon function exerted by proteins in the various steps of the hereditary process—to re-discuss the question whether the nucleic acids are the sole repositories of relevant information as assumed in the information theory of heredity. The evidence I here present of a crucial role for molecular chaperones in the folding of nascent proteins, as well as in DNA duplication, RNA folding and gene control, suggests that the family of proteins (...)
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  • The infinite regress of optimization.Philippe Mongin - 1991 - Behavioral and Brain Sciences 14 (2):229-230.
    A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.
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  • Two dynamic criteria for validating claims of optimality.Geoffrey F. Miller - 1991 - Behavioral and Brain Sciences 14 (2):228-229.
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  • Complexity and optimality.Dauglas A. Miller & Steven W. Zucker - 1991 - Behavioral and Brain Sciences 14 (2):227-228.
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  • Straining the word “optimal”.James E. Mazur - 1991 - Behavioral and Brain Sciences 14 (2):227-227.
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  • The example of psychology: Optimism, not optimality.Daniel S. Levine - 1991 - Behavioral and Brain Sciences 14 (2):225-226.
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  • Why optimality is not worth arguing about.Stephen E. G. Lea - 1991 - Behavioral and Brain Sciences 14 (2):225-225.
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  • Natural science, social science and optimality.Oleg Larichev - 1991 - Behavioral and Brain Sciences 14 (2):224-225.
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  • Reports of the death of the Gene are greatly exaggerated.Rob Knight - 2007 - Biology and Philosophy 22 (2):293-306.
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  • Entropy of knowledge.Hillary Jay Kelley - 1969 - Philosophy of Science 36 (2):178-196.
    Entropy is proposed as a concept which in its broader scope can contribute to the study of the General Information System. This paper attempts to identify a few fundamental subconcepts and LEMMAS which will serve to facilitate further study of system order. The paper discusses: partitioning order into logical and arbitrary kinds; the relationship of order to pattern; and suggested approaches to evaluating and improving the General Information System.
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  • Heritable Epigenetic Changes Alter Transgenerational Waveforms Maintained by Cycling Stores of Information.Antony M. Jose - 2020 - Bioessays 42 (7):1900254.
    Our view of heredity can potentially be distorted by the ease of introducing heritable changes in the replicating gene sequences but not in the cycling assembly of regulators around gene sequences. Here, key experiments that have informed the understanding of heredity are reinterpreted to highlight this distortion and the possible variety of heritable changes are considered. Unlike heritable genetic changes, which are always associated with mutations in gene sequence, heritable epigenetic changes can be associated with physical or chemical changes in (...)
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  • Personality and epistemology: Cognitive social learning theory as a philosophy of science.James W. Jones - 1989 - Zygon 24 (1):23-38.
    . Implicit in the cognitive social learning model of personality as articulated by Walter Mischel, Albert Bandura, and others, is an epistemology which emphasizes the activity of the mind in the construction of knowledge. Using Mischel's five person variables as an outline, the epistemic implications of this model of personality are developed and then illustrated by application to William James's typology of the religious personality and to the current debate over hermeneutic and empirical approaches to studying human behavior. This approach (...)
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  • Types of optimality: Who is the steersman?Michael E. Hyland - 1991 - Behavioral and Brain Sciences 14 (2):223-224.
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  • “Surprise” and the Bayesian Brain: Implications for Psychotherapy Theory and Practice.Jeremy Holmes & Tobias Nolte - 2019 - Frontiers in Psychology 10.
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  • Optimality and constraint.David A. Helweg & Herbert L. Roitblat - 1991 - Behavioral and Brain Sciences 14 (2):222-223.
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  • Unlocking the Black box between genotype and phenotype: Cell condensations as morphogenetic (modular) units. [REVIEW]Brian K. Hall - 2003 - Biology and Philosophy 18 (2):219-247.
    Embryonic development and ontogeny occupy whatis often depicted as the black box betweengenes – the genotype – and the features(structures, functions, behaviors) of organisms– the phenotype; the phenotype is not merelya one-to-one readout of the genotype. Thegenes home, context, and locus of operation isthe cell. Initially, in ontogeny, that cell isthe single-celled zygote. As developmentensues, multicellular assemblages of like cells(modules) progressively organized as germlayers, embryonic fields, anlage,condensations, or blastemata, enable genes toplay their roles in development and evolution.As modules, condensations are (...)
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  • Brain research and the social self in a technological culture.Paul T. Durbin - 2017 - AI and Society 32 (2):253-260.
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