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  1. 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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  • 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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  • Economic Models as Cultural Artifacts: A Philosophical Primer.Jarosław Boruszewski & Krzysztof Nowak-Posadzy - 2021 - Filozofia Nauki 29 (3):63-87.
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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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  • Energy: Learning from the Past.Fabio Bevilacqua - 2014 - Science & Education 23 (6):1231-1243.
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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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  • Optimality and human memory.John R. Anderson - 1991 - Behavioral and Brain Sciences 14 (2):215-216.
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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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  • 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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  • Should the quest for optimality worry us?Nils-Eric Sahlin - 1991 - Behavioral and Brain Sciences 14 (2):231-231.
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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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  • Don't just sit there, optimise something.J. H. P. Paelinck - 1991 - Behavioral and Brain Sciences 14 (2):230-230.
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  • The syllogism of neuro-economics.Camillo Padoa-Schioppa - 2008 - Economics and Philosophy 24 (3):449-457.
    If neuroscience is to contribute to economics, it will do so by the way of psychology. Neural data can and do lead to better psychological theories, and psychological insights can and do lead to better economic models. Hence, neuroscience can in principle contribute to economics. Whether it actually will do so is an empirical question and the jury is still out. Economics currently faces theoretical and empirical challenges analogous to those faced by physics at the turn of the twentieth century (...)
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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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  • Economics, Equilibrium Methods, and Multi-Scale Modeling.Jennifer Jhun - 2019 - Erkenntnis 86 (2):457-472.
    In this paper, I draw a parallel between the stability of physical systems and that of economic ones, such as the US financial system. I argue that the use of equilibrium assumptions is central to the analysis of dynamic behavior for both kinds of systems, and that we ought to interpret such idealizing strategies as footholds for causal exploration and explanation. Our considerations suggest multi-scale modeling as a natural home for such reasoning strategies, which can provide a backdrop for the (...)
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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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  • Optimality and constraint.David A. Helweg & Herbert L. Roitblat - 1991 - Behavioral and Brain Sciences 14 (2):222-223.
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  • The Methodological Status of 'Common Sense' in Economic Theory.Mackinnon Lauchlan - manuscript
    The present work was intended originally as a chapter for my January 2006 Ph.D dissertation, but now is essentially a 'working paper.' As is well known, economists make a number of abstract and unrealistic assumptions, such as for example characterising the economic agent as a rational maximiser. The present paper is concerned with assessing the methodological status of every-day common-sense observations in relation to such abstract and unrealistic assumptions. Following Popper and Hume, I propose a theoretical framework in which to (...)
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  • Exploration modes and its impact on industry profitability.L. Biggiero - 2010 - In Marisa Faggini, Concetto Paolo Vinci, Antonio Abatemarco, Rossella Aiello, F. T. Arecchi, Lucio Biggiero, Giovanna Bimonte, Sergio Bruno, Carl Chiarella, Maria Pia Di Gregorio, Giacomo Di Tollo, Simone Giansante, Jaime Gil Aluja, A. I͡U Khrennikov, Marianna Lyra, Riccardo Meucci, Guglielmo Monaco, Giancarlo Nota, Serena Sordi, Pietro Terna, Kumaraswamy Velupillai & Alessandro Vercelli (eds.), Decision Theory and Choices: A Complexity Approach. Springer Verlag Italia. pp. 83--115.
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  • Reflections on the Green Economy (Redemption of the Principles of Mill and Pigou): A View of a Brazilian Environmentalist.João Batista Drummond Câmara - 2014 - Journal of Environmental Protection 5:1153-1168.
    The current context of global efforts in the pursuit of sustainable development can be characterized by the perception of the scientific-technological losses of ecosystems and ecosystem services and their consequences for the survival of humanity in the face of threats of imbalances in the basic conditions for survival such as food production, the environmental quality, natural control of pests and diseases, loses of biodiversity and climate changes. Some recent initiatives at global, regional and local level are pointed and some conceptual (...)
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