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  1. 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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  • Automatic decision-making and reliability in robotic systems: some implications in the case of robot weapons.Roberto Cordeschi - 2013 - AI and Society 28 (4):431-441.
    In this article, I shall examine some of the issues and questions involved in the technology of autonomous robots, a technology that has developed greatly and is advancing rapidly. I shall do so with reference to a particularly critical field: autonomous military robotic systems. In recent times, various issues concerning the ethical implications of these systems have been the object of increasing attention from roboticists, philosophers and legal experts. The purpose of this paper is not to deal with these issues, (...)
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  • A brief history of connectionism and its psychological implications.S. F. Walker - 1990 - AI and Society 4 (1):17-38.
    Critics of the computational connectionism of the last decade suggest that it shares undesirable features with earlier empiricist or associationist approaches, and with behaviourist theories of learning. To assess the accuracy of this charge the works of earlier writers are examined for the presence of such features, and brief accounts of those found are given for Herbert Spencer, William James and the learning theorists Thorndike, Pavlov and Hull. The idea that cognition depends on associative connections among large networks of neurons (...)
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  • (1 other version)The discovery of the artificial: some protocybernetic developments 1930-1940.Roberto Cordeschi - 1991 - Artificial Intelligence and Society 5 (3):218-238.
    In this paper I start from a definition of “culture of the artificial” which might be stated by referring to the background of philosophical, methodological, pragmatical assumptions which characterizes the development of the information processing analysis of mental processes and of some trends in contemporary cognitive science: in a word, the development of AI as a candidate science of mind. The aim of this paper is to show how (with which plausibility and limitations) the discovery of the mentioned background might (...)
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  • (1 other version)Mediation theory and the problem of psychological discourse on 'inner' events: part II.Gottfried Seebaß - unknown
    The present article attempts to investigate the 'philosophical foundations' of psychology and thereby of the social sciences in general with regard to a central problem, viz. the question of the 'inner'. It does this with special critical reference to an authoritative psychological theory, viz. the so-called 'mediation theory', and tries to show the necessity of interdisciplinary clarification. In the first part mediation theory was introduced as a variant of psychological behaviorism which attempts to substitute for the untenable total neglect of (...)
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  • Cognitive maps and the language of thought.Michael Rescorla - 2009 - British Journal for the Philosophy of Science 60 (2):377-407.
    Fodor advocates a view of cognitive processes as computations defined over the language of thought (or Mentalese). Even among those who endorse Mentalese, considerable controversy surrounds its representational format. What semantically relevant structure should scientific psychology attribute to Mentalese symbols? Researchers commonly emphasize logical structure, akin to that displayed by predicate calculus sentences. To counteract this tendency, I discuss computational models of navigation drawn from probabilistic robotics. These models involve computations defined over cognitive maps, which have geometric rather than logical (...)
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  • Clark Hull, Robert Cummins, and functional analysis.Ron Amundson & Laurence D. Smith - 1984 - Philosophy of Science 51 (December):657-666.
    Robert Cummins has recently used the program of Clark Hull to illustrate the effects of logical positivist epistemology upon psychological theory. On Cummins's account, Hull's theory is best understood as a functional analysis, rather than a nomological subsumption. Hull's commitment to the logical positivist view of explanation is said to have blinded him to this aspect of this theory, and thus restricted its scope. We will argue that this interpretation of Hull's epistemology, though common, is mistaken. Hull's epistemological views were (...)
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  • The physical basis of memory.C. R. Gallistel - 2021 - Cognition 213 (C):104533.
    Neuroscientists are searching for the engram within the conceptual framework established by John Locke's theory of mind. This framework was elaborated before the development of information theory, before the development of information processing machines and the science of computation, before the discovery that molecules carry hereditary information, before the discovery of the codon code and the molecular machinery for editing the messages written in this code and translating it into transcription factors that mark abstract features of organic structure such as (...)
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  • Psychological Mechanisms.Ulrich Koch & Kelso Cratsley - 2020 - In V. Zeigler-Hill & T. Shackelford (eds.), Encyclopedia of Personality and Individual Differences. pp. 4145-4154.
    In the most inclusive sense, psychological mechanisms offer a type of causal explanation of mental states and behavior, often with reference to underlying processes, systems, activities, or entities. By postulating and investigating such mechanisms, researchers have sought explanations of a wide range of psychological phenomena. However, the concept has been deployed in dramatically different ways, with very different meanings, depending upon the particular school or tradition of psychology (and specific research program therein). In fact, usage has been so diverse as (...)
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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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  • Don't just sit there, optimise something.J. H. P. Paelinck - 1991 - Behavioral and Brain Sciences 14 (2):230-230.
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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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  • 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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  • Vaulting optimality.Peter Dayan & Jon Oberlander - 1991 - Behavioral and Brain Sciences 14 (2):221-222.
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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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  • Optimality as a mathematical rhetoric for zeroes.Fred L. Bookstein - 1991 - Behavioral and Brain Sciences 14 (2):216-217.
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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 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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  • Must cognition be representational?William Ramsey - 2017 - Synthese 194 (11):4197-4214.
    In various contexts and for various reasons, writers often define cognitive processes and architectures as those involving representational states and structures. Similarly, cognitive theories are also often delineated as those that invoke representations. In this paper, I present several reasons for rejecting this way of demarcating the cognitive. Some of the reasons against defining cognition in representational terms are that doing so needlessly restricts our theorizing, it undermines the empirical status of the representational theory of mind, and it encourages wildly (...)
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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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  • Optimality as a prescriptive tool.Alexander H. G. Rinnooy Kan - 1991 - Behavioral and Brain Sciences 14 (2):230-231.
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  • Organisms, scientists and optimality.Michael Davison - 1991 - Behavioral and Brain Sciences 14 (2):220-221.
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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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  • The cognitive map debate in insects: A historical perspective on what is at stake.Kelle Dhein - 2023 - Studies in History and Philosophy of Science Part A 98 (C):62-79.
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  • Optimality and human memory.John R. Anderson - 1991 - Behavioral and Brain Sciences 14 (2):215-216.
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  • Neurophysiological Effects Associated With Subliminal Conditioning of Appetite Motivations.Micah Amd & Sylvain Baillet - 2019 - Frontiers in Psychology 10.
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  • (1 other version)The discovery of the artificial. Some protocybernetic developments 1930–1940.Roberto Cordeschi - 1991 - AI and Society 5 (3):218-238.
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  • Criteria for optimality.Michel Cabanac - 1991 - Behavioral and Brain Sciences 14 (2):218-218.
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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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  • The example of psychology: Optimism, not optimality.Daniel S. Levine - 1991 - Behavioral and Brain Sciences 14 (2):225-226.
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  • On the Conceptual and Linguistic Activity of Psychologists: The Study of Behavior from the 1890s to the 1990s and beyond. [REVIEW]David E. Leary - 2004 - Behavior and Philosophy 32 (1):13 - 35.
    In the early twentieth century psychology became the study of "behavior." This article reviews developments within animal psychology, functional psychology, and American society and culture that help explain how a term rarely used in the first years of the century became not only an accepted scientific concept but even, for many, an all-encompassing label for the entire subject matter of the discipline. The subsequent conceptual and linguistic activity of John B. Watson, Edward C. Tolman, Clark L. Hull, and B.F. Skinner, (...)
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  • Prediction in chaotic social, economic, and political conditions: The conflict between traditional chaos theory and the psychology of prediction, and some implications for general evolution theory.David Loye - 1995 - World Futures 44 (1):15-31.
    (1995). Prediction in chaotic social, economic, and political conditions: The conflict between traditional chaos theory and the psychology of prediction, and some implications for general evolution theory. World Futures: Vol. 44, No. 1, pp. 15-31.
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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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  • 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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  • Optimal confusion.Stephanie Stolarz-Fantino & Edmund Fantino - 1991 - Behavioral and Brain Sciences 14 (2):234-234.
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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 and optimality.Dauglas A. Miller & Steven W. Zucker - 1991 - Behavioral and Brain Sciences 14 (2):227-228.
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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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  • Avoid the push-pull dilemma in explanation.Kenneth M. Steele - 1991 - Behavioral and Brain Sciences 14 (2):233-234.
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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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  • Straining the word “optimal”.James E. Mazur - 1991 - Behavioral and Brain Sciences 14 (2):227-227.
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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 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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