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  1. Calibrating Generative Models: The Probabilistic Chomsky-Schützenberger Hierarchy.Thomas Icard - 2020 - Journal of Mathematical Psychology 95.
    A probabilistic Chomsky–Schützenberger hierarchy of grammars is introduced and studied, with the aim of understanding the expressive power of generative models. We offer characterizations of the distributions definable at each level of the hierarchy, including probabilistic regular, context-free, (linear) indexed, context-sensitive, and unrestricted grammars, each corresponding to familiar probabilistic machine classes. Special attention is given to distributions on (unary notations for) positive integers. Unlike in the classical case where the "semi-linear" languages all collapse into the regular languages, using analytic tools (...)
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  • Representation in Cognitive Science.Nicholas Shea - 2018 - Oxford University Press.
    How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.
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  • Why one model is never enough: a defense of explanatory holism.Hochstein Eric - 2017 - Biology and Philosophy 32 (6):1105-1125.
    Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...)
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  • Intentional Models as Essential Scientific Tools.Eric Hochstein - 2013 - International Studies in the Philosophy of Science 27 (2):199-217.
    In this article, I argue that the use of scientific models that attribute intentional content to complex systems bears a striking similarity to the way in which statistical descriptions are used. To demonstrate this, I compare and contrast an intentional model with a statistical model, and argue that key similarities between the two give us compelling reasons to consider both as a type of phenomenological model. I then demonstrate how intentional descriptions play an important role in scientific methodology as a (...)
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  • When No Laughing Matter Is No Laughing Matter: The Challenges in Developing a Cognitive Theory of Humor.Eric Hochstein - 2021 - The Philosophy of Humor Yearbook 2 (1):87-110.
    This paper explores the current obstacles that a cognitive theory of humor faces. More specifically, I argue that the nebulous and ill-defined nature of humor makes it difficult to tell what counts as clear instances of, and deficits in, the phenomenon.Without getting clear on this, we cannot identify the underlying cognitive mechanisms responsible for humor. Moreover, being too quick to draw generalizations regarding the ubiquity of humor, or its uniqueness to humans, without substantially clarifying the phenomenon and its occurrences is (...)
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  • Empirical Evidence and the Multiple Realization of Mental Kinds.Danny Booth - 2018 - Dissertation, University of Western Ontario
    This thesis explores the use of the concept 'realization' in the philosophy of mind. The primary focus is on the role realization plays in assessing or opposing identity theory. The history of the use of the concept of realization in the philosophy of mind is reviewed, and from that a set of desiderata to be used for assessing accounts of realization is extracted. The desiderata are applied to a sample account of realization proposed by Sydney Shoemaker. (2007) Next the application (...)
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  • Fundamentals of whole brain emulation: State, transition and update representations.Randal A. Koene - 2012 - International Journal of Machine Consciousness 4 (01):5-21.
    Whole brain emulation aims to re-implement functions of a mind in another computational substrate with the precision needed to predict the natural development of active states in as much as the influence of random processes allows. Furthermore, brain emulation does not present a possible model of a function, but rather presents the actual implementation of that function, based on the details of the circuitry of a specific brain. We introduce a notation for the representations of mind state, mind transition functions (...)
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  • Minds, models and mechanisms: a new perspective on intentional psychology.Eric Hochstein - 2012 - Journal of Experimental & Theoretical Artificial Intelligence 24 (4):547-557.
    In this article, I argue that intentional psychology (i.e. the interpretation of human behaviour in terms of intentional states and propositional attitudes) plays an essential role in the sciences of the mind. However, this role is not one of identifying scientifically respectable states of the world. Rather, I argue that intentional psychology acts as a type of phenomenological model, as opposed to a mechanistic one. I demonstrate that, like other phenomenological models in science, intentional psychology is a methodological tool with (...)
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  • Static-Dynamic Hybridity in Dynamical Models of Cognition.Naftali Weinberger & Colin Allen - 2022 - Philosophy of Science 89 (2):283-301.
    Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representations of a system.
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  • (1 other version)Dynamicism, radical enactivism, and representational cognitive processes: The case of subitization.Misha Ash & Rex Welshon - 2020 - Tandf: Philosophical Psychology 33 (8):1096-1120.
    Volume 33, Issue 8, November 2020, Page 1096-1120.
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  • ‘Consciousness’ and Brain Functions: A Re-look from Functionalist Perspective.Suresh Muruganandam - 2022 - International Journal of Philosophy 10 (1):1.
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  • Understanding and augmenting human morality: An introduction to the ACTWith model of conscience.Jeffrey White - 2010 - In W. Carnielli L. Magnani (ed.), Model-Based Reasoning in Science and Technology. pp. 607--621.
    Recent developments, both in the cognitive sciences and in world events, bring special emphasis to the study of morality. The cognitive sciences, spanning neurology, psychology, and computational intelligence, offer substantial ad- vances in understanding the origins and purposes of morality. Meanwhile, world events urge the timely synthesis of these insights with traditional ac- counts that can be easily assimilated and practically employed to augment moral judgment, both to solve current problems and to direct future action. The object of the following (...)
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  • What do mirror neurons mirror?Sebo Uithol, Iris van Rooij, Harold Bekkering & Pim Haselager - 2011 - Philosophical Psychology 24 (5):607 - 623.
    Single cell recordings in monkeys provide strong evidence for an important role of the motor system in action understanding. This evidence is backed up by data from studies of the (human) mirror neuron system using neuroimaging or TMS techniques, and behavioral experiments. Although the data acquired from single cell recordings are generally considered to be robust, several debates have shown that the interpretation of these data is far from straightforward. We will show that research based on single-cell recordings allows for (...)
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  • (1 other version)The dynamical renaissance in neuroscience.Luis H. Favela - 2020 - Synthese 199 (1-2):2103-2127.
    Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...)
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  • One mechanism, many models: a distributed theory of mechanistic explanation.Eric Hochstein - 2016 - Synthese 193 (5):1387-1407.
    There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that individual models (...)
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  • (1 other version)Dynamicism, radical enactivism, and representational cognitive processes: The case of subitization.Misha Ash & Rex Welshon - 2020 - Philosophical Psychology 33 (8):1096-1120.
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  • The Complex Systems Approach: Rhetoric or Revolution.Chris Eliasmith - 2012 - Topics in Cognitive Science 4 (1):72-77.
    The complex systems approach (CSA) to characterizing cognitive function is purported to underlie a conceptual and methodological revolution by its proponents. I examine one central claim from each of the contributed papers and argue that the provided examples do not justify calls for radical change in how we do cognitive science. Instead, I note how currently available approaches in ‘‘standard’’ cognitive science are adequate (or even more appropriate) for understanding the CSA provided examples.
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