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  1. Neural Representations Beyond “Plus X”.Alessio Plebe & Vivian M. De La Cruz - 2018 - Minds and Machines 28 (1):93-117.
    In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...)
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  • Commentary: Getting into predictive processing's great guessing game: Bootstrap heaven or hell?Michał Piekarski - 2017 - Frontiers in Psychology 8.
  • The Hard Problem Of Content: Solved (Long Ago).Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 41 (1):73-88.
    In this paper, I argue that even if the Hard Problem of Content, as identified by Hutto and Myin, is important, it was already solved in natu- ralized semantics, and satisfactory solutions to the problem do not rely merely on the notion of information as covariance. I point out that Hutto and Myin have double standards for linguistic and mental representation, which leads to a peculiar inconsistency. Were they to apply the same standards to basic and linguistic minds, they would (...)
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  • Much ado about nothing? Why going non-semantic is not merely semantics.Daniel D. Hutto & Erik Myin - 2018 - Philosophical Explorations 21 (2):187-203.
    This paper argues that deciding on whether the cognitive sciences need a Representational Theory of Mind matters. Far from being merely semantic or inconsequential, the answer we give to the RTM-question makes a difference to how we conceive of minds. How we answer determines which theoretical framework the sciences of mind ought to embrace. The structure of this paper is as follows. Section 1 outlines Rowlands’s argument that the RTM-question is a bad question and that attempts to answer it, one (...)
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  • The problem with appealing to history in defining neural representations.Ori Hacohen - 2022 - European Journal for Philosophy of Science 12 (3):1-17.
    Representations seem to play a major role in many neuroscientific explanations. Philosophers have long attempted to properly define what it means for a neural state to be a representation of a specific content. Teleosemantic theories of content which characterize representations, in part, by appealing to a historical notion of function, are often regarded as our best path towards an account of neural representations. This paper points to the anti-representationalist consequences of these accounts. I argue that assuming such teleosemantic views will (...)
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  • Representation of Reality: Humans, Other Living Organism and Intelligent Machines.Gordana Dodig-Crnkovic & Raffaela Giovagnoli (eds.) - 2017 - Heidelberg: Springer.
    In this book the editors invited prominent researchers with different perspectives and deep insights into the various facets of the relationship between reality and representation in the following three classes of agent: in humans, in other living beings, and in machines. -/- The book enriches our views on representation and deepens our understanding of its different aspects, a question that connects philosophy, computer science, logic, anthropology, psychology, sociology, neuroscience, linguistics, information and communication science, systems theory and engineering, computability, cybernetics, synthetic (...)
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  • Neural Representations Beyond “Plus X”.Vivian Cruz & Alessio Plebe - 2018 - Minds and Machines 28 (1):93-117.
    In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...)
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  • Enactivism, Radical Enactivism and Predictive Processing: What is Radical in Cognitive Science?Robert W. Clowes & Klaus Gärtner - 2017 - Kairos 18 (1):54-83.
    According to Enactivism, cognition should be understood in terms of a dynamic interaction between an acting organism and its environment. Further, this view holds that organisms do not passively receive information from this environment, they rather selectively create this environment by engaging in interaction with the world. Radical Enactivism adds that basic cognition does so without entertaining representations and hence that representations are not an essential constituent of cognition. Some proponents think that getting rid of representations amounts to a revolutionary (...)
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  • Mental Misrepresentation in Non-human Psychopathology.Krystyna Bielecka & Mira Marcinów - 2017 - Biosemiotics 10 (2):195-210.
    In this paper, we defend a representational approach to at least some kinds of non-human psychopathology. Mentally-ill non-human minds, in particular in delusions, obsessive-compulsive disorders and similar cognitive states, are traditionally understood in purely behavioral terms. In contrast, we argue that non-human mental psychopathology should be at least sometimes not only ascribed contentful mental representation but also understood as really having these states. To defend this view, we appeal to the interactivist account of mental representation, which is a kind of (...)
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  • Biopsychologiczne podstawy poznania geometrycznego.Mateusz Hohol - 2018 - Philosophical Problems in Science 64:137-165.
    In this review-paper, I focus on biopsychological foundations of geometric cognition. Starting from the Kant’s views on mathematics, I attempt to show that contemporary cognitive scientists, alike the famous philosopher, recognize mutual relationships of visuospatial processing and geometric cognition. What I defend is a claim that Tinbergen’s explanatory questions are the most fruitful tool for explaining our “hardwired,” and thus shared with other animals, Euclidean intuitions, which manifest themselves in spatial navigation and shape recognition. I claim, however, that these “hardwired (...)
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