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  1. The Intention of Intention.Ramón Casares - manuscript
    For Putnam in "Representation and Reality", there cannot be any intentional science, thus dooming cognitive science. His argument is that intentional concepts are functional, and that functionalism cannot explain anything because "everything has every functional organization", providing a proof. Analyzing his proof, we find that Putnam is assuming an ideal interpreting subject who can compute effortlessly and who is not intentional. But the subject doing science is a human being, and we are not that way. Therefore, in order to save (...)
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  2. Representation Re-construed: Construal-based Norms for Ascribing Natural Representations.Akagi Mikio - manuscript
    Many philosophers worry that cognitive scientists apply the concept REPRESENTATION too liberally. For example, William Ramsey argues that scientists often ascribe natural representations according to the “receptor notion,” a causal account with absurd consequences. I rehabilitate the receptor notion by augmenting it with a background condition: that natural representations are ascribed only to systems construed as organisms. This Organism-Receptor account rationalizes our existing conceptual practice, including the fact that scientists in fact reject Ramsey’s absurd consequences. The Organism-Receptor account raises some (...)
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  3. Information and the function of neurons.Marc Burock - 2011
    Many of us consider it uncontroversial that information processing is a natural function of the brain. Since functions in biology are only won through empirical investigation, there should be a significant body of unambiguous evidence that supports this functional claim. Before we can interpret the evidence, however, we must ask what it means for a biological system to process information. Although a concept of information is generally accepted in the neurosciences without critique, in other biological sciences applications of information, despite (...)
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  4. The biology of consciousness: Comparative review of Israel Rosenfield, the strange, familiar, and forgotten: An anatomy of consciousness and Gerald M. Edelman, bright air, brilliant fire: On the matter of the mind.W. J. Clancey - forthcoming - Philosophical Explorations.
    For many years, most AI researchers and cognitive scientists have reserved the topic of consciousness for after dinner conversation. Like "intuition," the idea of consciousness appeared to be too vague or general to be a good starting place for understanding cognition. Work on narrowly-defined problems in specialized domains such as medicine and manufacturing focused our concerns on the nature of representation, memory, strategies for problem-solving, and learning. Some writers, notably Ornstein and Hofstadter, continued to explore the ideas, but implications for (...)
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  5. Cognition Beyond the Brain: Computation, Interactivity and Human Artifice (2nd ed.).Stephen Cowley & Frederic Vallée-Tourangeau (eds.) - forthcoming - Springer.
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  6. Troubles with mathematical contents.Marco Facchin - forthcoming - Philosophical Psychology.
    To account for the explanatory role representations play in cognitive science, Egan’s deflationary account introduces a distinction between cognitive and mathematical contents. According to that account, only the latter are genuine explanatory posits of cognitive-scientific theories, as they represent the arguments and values cognitive devices need to represent to compute. Here, I argue that the deflationary account suffers from two important problems, whose roots trace back to the introduction of mathematical contents. First, I will argue that mathematical contents do not (...)
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  7. Does Artificial Intelligence Use Private Language?Ryan Miller - forthcoming - In Proceedings of the International Ludwig Wittgenstein Symposium 2021. Vienna: Lit Verlag.
    Wittgenstein’s Private Language Argument holds that language requires rule-following, rule following requires the possibility of error, error is precluded in pure introspection, and inner mental life is known only by pure introspection, thus language cannot exist entirely within inner mental life. Fodor defends his Language of Thought program against the Private Language Argument with a dilemma: either privacy is so narrow that internal mental life can be known outside of introspection, or so broad that computer language serves as a counter-example. (...)
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  8. Time-consciousness in computational phenomenology: a temporal analysis of active inference.Juan Diego Bogotá & Zakaria Djebbara - 2023 - Neuroscience of Consciousness 2023 (1):niad004.
    Time plays a significant role in science and everyday life. Despite being experienced as a continuous flow, computational models of consciousness are typically restricted to a sequential temporal structure. This difference poses a serious challenge for computational phenomenology—a novel field combining phenomenology and computational modelling. By analysing the temporal structure of the active inference framework, we show that an integrated continuity of time can be achieved by merging Husserlian temporality with a sequential order of time. We also show that a (...)
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  9. A Model Solution: On the Compatibility of Predictive Processing and Embodied Cognition.Luke Kersten - 2023 - Minds and Machines 33 (1):113-134.
    Predictive processing (PP) and embodied cognition (EC) have emerged as two influential approaches within cognitive science in recent years. Not only have PP and EC been heralded as “revolutions” and “paradigm shifts” but they have motivated a number of new and interesting areas of research. This has prompted some to wonder how compatible the two views might be. This paper looks to weigh in on the issue of PP-EC compatibility. After outlining two recent proposals, I argue that further clarity can (...)
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  10. Why is Generative Grammar Recursive?Fintan Mallory - 2023 - Erkenntnis 88 (7):3097-3111.
    A familiar argument goes as follows: natural languages have infinitely many sentences, finite representation of infinite sets requires recursion; therefore any adequate account of linguistic competence will require some kind of recursive device. The first part of this paper argues that this argument is not convincing. The second part argues that it was not the original reason recursive devices were introduced into generative linguistics. The real basis for the use of recursive devices stems from a deeper philosophical concern; a grammar (...)
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  11. The language-of-thought hypothesis as a working hypothesis in cognitive science.Jake Quilty-Dunn, Nicolas Porot & Eric Mandelbaum - 2023 - Behavioral and Brain Sciences 46:e292.
    The target article attempted to draw connections between broad swaths of evidence by noticing a common thread: Abstract, symbolic, compositional codes, that is, language-of-thoughts (LoTs). Commentators raised concerns about the evidence and offered fascinating extensions to areas we overlooked. Here we respond and highlight the many specific empirical questions to be answered in the next decade and beyond.
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  12. Organized representations forming a computationally useful processing structure.Nicholas Shea - 2023 - Synthese 202 (6):1-20.
    Peter Godfrey-Smith recently introduced the idea of representational ‘organization’. When a collection of representations form an organized family, similar representational vehicles carry similar contents. For example, where neural firing rate represents numerosity (an analogue magnitude representation), similar firing rates represent similar numbers of items. Organization has been elided with structural representation, but the two are in fact distinct. An under-appreciated merit of representational organization is the way it facilitates computational processing. Representations from different organized families can interact, for example to (...)
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  13. Massive Modularity: An Ontological Hypothesis or an Adaptationist Discovery Heuristic?David Villena - 2023 - International Studies in the Philosophy of Science 36 (4):317-334.
    Cognitive modules are internal mental structures. Some theorists and empirical researchers hypothesise that the human mind is either partially or massively comprised of structures that are modular in nature. Is the massive modularity of mind hypothesis a cogent view about the ontological nature of human mind or is it, rather, an effective/ineffective adaptationist discovery heuristic for generating predictively successful hypotheses about both heretofore unknown psychological traits and unknown properties of already identified psychological traits? Considering the inadequacies of the case in (...)
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  14. Formal thought disorder and logical form: A symbolic computational model of terminological knowledge.Luis M. Augusto & Farshad Badie - 2022 - Journal of Knowledge Structures and Systems 3 (4):1-37.
    Although formal thought disorder (FTD) has been for long a clinical label in the assessment of some psychiatric disorders, in particular of schizophrenia, it remains a source of controversy, mostly because it is hard to say what exactly the “formal” in FTD refers to. We see anomalous processing of terminological knowledge, a core construct of human knowledge in general, behind FTD symptoms and we approach this anomaly from a strictly formal perspective. More specifically, we present here a symbolic computational model (...)
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  15. Mind as Machine: The Influence of Mechanism on the Conceptual Foundations of the Computer Metaphor.Pavel Baryshnikov - 2022 - RUDN Journal of Philosophy 26 (4):755-769.
    his article will focus on the mechanistic origins of the computer metaphor, which forms the conceptual framework for the methodology of the cognitive sciences, some areas of artificial intelligence and the philosophy of mind. The connection between the history of computing technology, epistemology and the philosophy of mind is expressed through the metaphorical dictionaries of the philosophical discourse of a particular era. The conceptual clarification of this connection and the substantiation of the mechanistic components of the computer metaphor is the (...)
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  16. Why not Both (but also, Neither)? Markov Blankets and the Idea of Enactive-Extended Cognition.Juan Diego Bogotá - 2022 - Constructivist Foundations 17 (3):233-235.
    I sympathize with Prosen’s conviction in integrating enactivism, the free-energy principle, and the extended-mind hypothesis. However, I show that he uses the concept of “boundary” ambiguously. By disambiguating it, I suggest that we can keep both Markov blankets and operational closure as ways of drawing the boundaries of a cognitive system. Nevertheless, from an enactive perspective, neither of those boundaries is a “cognitive” boundary.
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  17. Textos Selecionados de Filosofia da Cognição.Eros Moreira de Carvalho - 2022 - Pelotas: NEPFIL online.
    Coletânea de traduções de verbetes da SEP na área de Filosofia da Cognição organizada por Eros Carvalho (UFRGS). A obra contém os seguintes verbetes: "Ciência cognitiva", "A teoria computacional da mente", "Teorias teleológicas do conteúdo mental", "Modularidade da Mente", "Cognição Corporificada", "Emoção", e "Cognição Animal".
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  18. Everything and More: The Prospects of Whole Brain Emulation.Eric Mandelbaum - 2022 - Journal of Philosophy 119 (8):444-459.
    Whole Brain Emulation has been championed as the most promising, well-defined route to achieving both human-level artificial intelligence and superintelligence. It has even been touted as a viable route to achieving immortality through brain uploading. WBE is not a fringe theory: the doctrine of Computationalism in philosophy of mind lends credence to the in-principle feasibility of the idea, and the standing of the Human Connectome Project makes it appear to be feasible in practice. Computationalism is a popular, independently plausible theory, (...)
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  19. Free energy: a user’s guide.Stephen Francis Mann, Ross Pain & Michael D. Kirchhoff - 2022 - Biology and Philosophy 37 (4):1-35.
    Over the last fifteen years, an ambitious explanatory framework has been proposed to unify explanations across biology and cognitive science. Active inference, whose most famous tenet is the free energy principle, has inspired excitement and confusion in equal measure. Here, we lay the ground for proper critical analysis of active inference, in three ways. First, we give simplified versions of its core mathematical models. Second, we outline the historical development of active inference and its relationship to other theoretical approaches. Third, (...)
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  20. Against neuroclassicism: On the perils of armchair neuroscience.Alex Morgan - 2022 - Mind and Language 37 (3):329-355.
    Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue (...)
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  21. Explaining Machine Learning Decisions.John Zerilli - 2022 - Philosophy of Science 89 (1):1-19.
    The operations of deep networks are widely acknowledged to be inscrutable. The growing field of Explainable AI has emerged in direct response to this problem. However, owing to the nature of the opacity in question, XAI has been forced to prioritise interpretability at the expense of completeness, and even realism, so that its explanations are frequently interpretable without being underpinned by more comprehensive explanations faithful to the way a network computes its predictions. While this has been taken to be a (...)
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  22. Heterogeneous inferences with maps.Mariela Aguilera - 2021 - Synthese 199 (1-2):3805-3824.
    Since Tolman’s paper in 1948, psychologists and neuroscientists have argued that cartographic representations play an important role in cognition. These empirical findings align with some theoretical works developed by philosophers who promote a pluralist view of representational vehicles, stating that cognitive processes involve representations with different formats. However, the inferential relations between maps and representations with different formats have not been sufficiently explored. Thus, this paper is focused on the inferential relations between cartographic and linguistic representations. To that effect, we (...)
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  23. 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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  24. A new cognitive model of long-term memory for intentions.Thor Grünbaum, Franziska Oren & Søren Kyllingsbæk - 2021 - Cognition 215 (C):104817.
    In this paper, we propose a new mathematical model of retrieval of intentions from long-term memory. We model retrieval as a stochastic race between a plurality of potentially relevant intentions stored in long-term memory. Psychological theories are dominated by two opposing conceptions of the role of memory in temporally extended agency – as when a person has to remember to make a phone call in the afternoon because, in the morning, she promised she would do so. According to the Working (...)
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  25. Events, Event Prediction, and Predictive Processing.Jakob Hohwy, Augustus Hebblewhite & Tom Drummond - 2021 - Topics in Cognitive Science 13 (1):252-255.
    Events and event prediction are pivotal concepts across much of cognitive science, as demonstrated by the papers in this special issue. We first discuss how the study of events and the predictive processing framework may fruitfully inform each other. We then briefly point to some links to broader philosophical questions about events.
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  26. Brain electrical traits of logical validity.F. Salto - 2021 - Scientific Reports 11 (7892).
    Neuroscience has studied deductive reasoning over the last 20 years under the assumption that deductive inferences are not only de jure but also de facto distinct from other forms of inference. The objective of this research is to verify if logically valid deductions leave any cerebral electrical trait that is distinct from the trait left by non-valid deductions. 23 subjects with an average age of 20.35 years were registered with MEG and placed into a two conditions paradigm (100 trials for (...)
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  27. The dynamical renaissance in neuroscience.Luis H. Favela - 2020 - Synthese 1 (1):1-25.
    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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  28. Minds, Brains, and Capacities: Situated Cognition and Neo-Aristotelianism.Hans-Johann Https://Orcidorg909X Glock - 2020 - Frontiers in Psychology 11.
    This article compares situated cognition to contemporary Neo-Aristotelian approaches to the mind. The article distinguishes two components in this paradigm: an Aristotelian essentialism which is alien to situated cognition and a Wittgensteinian “capacity approach” to the mind which is not just congenial to it but provides important conceptual and argumentative resources in defending social cognition against orthodox cognitive science. It focuses on a central tenet of that orthodoxy. According to what I call “encephalocentrism,” cognition is primarily or even exclusively a (...)
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  29. Social Ontology: Time to Compute.Igor Mikhailov - 2020 - Vestnik Tomskogo Gosudarstvennogo Universiteta. Filosofiya, Sotsiologiya, Politologiya 1 (55):36-46.
    Discussions on the alleged methodological specificity of social knowledge are fueled to not the least extent by a kind of retarded position of the latter against technological advancements of natural and information science based on exact methods and formal or quantitative languages. It is more or less obvious that applicability of exact scientific methods to social disciplines is highly dependent on a chosen conception of social reality, i. e., on social ontology. In the article, the author critically approaches the ontological (...)
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  30. INFERENCE AND REPRESENTATION: PHILOSOPHICAL AND COGNITIVE ISSUES.Igor Mikhailov - 2020 - Vestnik Tomskogo Gosudarstvennogo Universiteta. Filosofiya, Sotsiologiya, Politologiya 1 (58):34-46.
    The paper is dedicated to particular cases of interaction and mutual impact of philosophy and cognitive science. Thus, philosophical preconditions in the middle of the 20th century shaped the newly born cognitive science as mainly based on conceptual and propositional representations and syntactical inference. Further developments towards neural networks and statistical representations did not change the prejudice much: many still believe that network models must be complemented with some extra tools that would account for proper human cognitive traits. I address (...)
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  31. Towards an Official Computational Thinking Education in Regular School Settings. Review of Computational Thinking Education, edited by Siu-Cheung Kong and Harold Abelson.Samet Okumus - 2020 - Constructivist Foundations 16 (1):129-132.
    The book provides a deep account of the use of computational thinking (CT) skills in education, with a focus on individual, social and cultural elements, and dives into issues foregrounding CT skills. Although the chapters of the book provide important educational and practical implications for the reader, methodological choices and the lack of theoretical connections of CT concepts curtail the use of CT skills in education, from a constructionist view.
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  32. Deep learning and cognitive science.Pietro Perconti & Alessio Plebe - 2020 - Cognition 203:104365.
    In recent years, the family of algorithms collected under the term ``deep learning'' has revolutionized artificial intelligence, enabling machines to reach human-like performances in many complex cognitive tasks. Although deep learning models are grounded in the connectionist paradigm, their recent advances were basically developed with engineering goals in mind. Despite of their applied focus, deep learning models eventually seem fruitful for cognitive purposes. This can be thought as a kind of biological exaptation, where a physiological structure becomes applicable for a (...)
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  33. AI-Completeness: Using Deep Learning to Eliminate the Human Factor.Kristina Šekrst - 2020 - In Sandro Skansi (ed.), Guide to Deep Learning Basics. Springer. pp. 117-130.
    Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...)
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  34. 类人猿或安卓会毁灭地球吗?*雷·库兹韦尔(2012年)关于如何创造心灵的评论 (Will Hominoids or Androids Destroy the Earth? —A Review of How to Create a Mind by Ray Kurzweil (2012)) (2019年修订版).Michael Richard Starks - 2020 - In 欢迎来到地球上的地狱: 婴儿,气候变化,比特币,卡特尔,中国,民主,多样性,养成基因,平等,黑客,人权,伊斯兰教,自由主义,繁荣,网络,混乱。饥饿,疾病,暴力,人工智能,战争. Las Vegas, NV USA: Reality Press. pp. 146-158.
    几年前,我通常可以从书名中分辨出什么,或者至少从章节标题中看出,会犯什么样的哲学错误,以及错误的频率。就名义上的科学著作而言,这些可能在很大程度上局限于某些章节,这些章节具有哲学意义或试图得出关于该作 品的意义或长期意义的一般性结论。然而,通常情况下,事实的科学问题慷慨地与哲学的胡言乱语,这些事实意味着什么。维特根斯坦在大约80年前描述的科学问题与各种语言游戏所描述的明确区别很少被考虑,因此人们交替 地被科学所震惊,并因它的不连贯而感到沮丧。分析。因此,这是与这个卷。 如果一个人要创造一个或多或少像我们一样的头脑,一个人需要有一个理性的逻辑结构,并理解两种思想体系(双过程理论)。如果一个人要对此进行哲学思考,就需要理解科学事实问题与语言如何在问题语境中工作,以及如何 避免还原主义和科学主义的陷阱的哲学问题之间的区别,但Kurzweil,如最学生的行为,基本上都是无知的。他被模型、理论和概念所陶醉,以及解释的冲动,而维特根斯坦向我们表明,我们只需要描述,理论、概念等 只是使用语言(语言游戏)的方式,只有它们有明确的价值测试(清晰的真理制造者,或约翰西尔(AI最著名的批评家)喜欢说,明确的满意条件(COS))。我试图在我最近的著作中对此作一个开端。 那些希望从现代两个系统的观点来看为人类行为建立一个全面的最新框架的人,可以查阅我的书《路德维希的哲学、心理学、Mind 和语言的逻辑结构》维特根斯坦和约翰·西尔的《第二部》(2019年)。那些对我更多的作品感兴趣的人可能会看到《会说话的猴子——一个末日星球上的哲学、心理学、科学、宗教和政治——文章和评论2006-201 9年第3次(2019年)和自杀乌托邦幻想21篇世纪4日 (2019) .
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  35. O "Frame Problem": a sensibilidade ao contexto como um desafio para teorias representacionais da mente.Carlos Barth - 2019 - Dissertation, Federal University of Minas Gerais
    Context sensitivity is one of the distinctive marks of human intelligence. Understanding the flexible way in which humans think and act in a potentially infinite number of circumstances, even though they’re only finite and limited beings, is a central challenge for the philosophy of mind and cognitive science, particularly in the case of those using representational theories. In this work, the frame problem, that is, the challenge of explaining how human cognition efficiently acknowledges what is relevant from what is not (...)
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  36. The quantization error in a Self-Organizing Map as a contrast and color specific indicator of single-pixel change in large random patterns.Birgitta Dresp-Langley - 2019 - Neural Networks 120:116-128..
    The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation time, highly meaningful changes across images in medical time series and in time series of satellite images. Here, the functional properties of the quantization error in SOM are explored further to show that the metric is capable of reliably discriminating between the finest differences in local contrast intensities and contrast signs. While this capability of the QE is (...)
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  37. A fresh look at research strategies in computational cognitive science: The case of enculturated mathematical problem solving.Regina E. Fabry & Markus Pantsar - 2019 - Synthese 198 (4):3221-3263.
    Marr’s seminal distinction between computational, algorithmic, and implementational levels of analysis has inspired research in cognitive science for more than 30 years. According to a widely-used paradigm, the modelling of cognitive processes should mainly operate on the computational level and be targeted at the idealised competence, rather than the actual performance of cognisers in a specific domain. In this paper, we explore how this paradigm can be adopted and revised to understand mathematical problem solving. The computational-level approach applies methods from (...)
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  38. Integrating computation into the mechanistic hierarchy in the cognitive and neural sciences.Lotem Elber-Dorozko & Oron Shagrir - 2019 - Synthese 199 (Suppl 1):43-66.
    It is generally accepted that, in the cognitive and neural sciences, there are both computational and mechanistic explanations. We ask how computational explanations can integrate into the mechanistic hierarchy. The problem stems from the fact that implementation and mechanistic relations have different forms. The implementation relation, from the states of an abstract computational system to the physical, implementing states is a homomorphism mapping relation. The mechanistic relation, however, is that of part/whole; the explaining features in a mechanistic explanation are the (...)
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  39. The physics of implementing logic: Landauer's principle and the multiple-computations theorem.Meir Hemmo & Orly Shenker - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 68:90-105.
    This paper makes a novel linkage between the multiple-computations theorem in philosophy of mind and Landauer’s principle in physics. The multiple-computations theorem implies that certain physical systems implement simultaneously more than one computation. Landauer’s principle implies that the physical implementation of “logically irreversible” functions is accompanied by minimal entropy increase. We show that the multiple-computations theorem is incompatible with, or at least challenges, the universal validity of Landauer’s principle. To this end we provide accounts of both ideas in terms of (...)
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  40. Bounded Rationality and Heuristics in Humans and in Artificial Cognitive Systems.Antonio Lieto - 2019 - Isonomía. Revista de Teoría y Filosofía Del Derecho 1 (4):1-21.
    In this paper I will present an analysis of the impact that the notion of “bounded rationality”, introduced by Herbert Simon in his book “Administrative Behavior”, produced in the field of Artificial Intelligence (AI). In particular, by focusing on the field of Automated Decision Making (ADM), I will show how the introduction of the cognitive dimension into the study of choice of a rational (natural) agent, indirectly determined - in the AI field - the development of a line of research (...)
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  41. Del hombre-máquina a la máquina-hombre: materialismo, mecanicismo y transhumanismo.Martín López Corredoira - 2019 - Naturaleza y Libertad. Revista de Estudios Interdisciplinares 12:179-190.
    El materialismo de la Edad Moderna nos describe al hombre como una máquina, comparable a un complejo artilugio mecánico. Cabe entonces imaginar que una máquina no-biológica pueda constituir un ser pensante como lo son los seres humanos, e incluso cabría pensar en la posibilidad de codificación de una mente humana real para su posterior trasvase a un sustrato artificial. Considero que estas últimas posiciones son más propias de la cultura friki o de amantes de la ciencia ficción que de una (...)
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  42. Cognitive and Computational Complexity: Considerations from Mathematical Problem Solving.Markus Pantsar - 2019 - Erkenntnis 86 (4):961-997.
    Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in cognitive processes that (...)
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  43. Intellectualism and the argument from cognitive science.Arieh Schwartz & Zoe Drayson - 2019 - Philosophical Psychology 32 (5):662-692.
    Intellectualism is the claim that practical knowledge or ‘know-how’ is a kind of propositional knowledge. The debate over Intellectualism has appealed to two different kinds of evidence, semantic and scientific. This paper concerns the relationship between Intellectualist arguments based on truth-conditional semantics of practical knowledge ascriptions, and anti-Intellectualist arguments based on cognitive science and propositional representation. The first half of the paper argues that the anti-Intellectualist argument from cognitive science rests on a naturalistic approach to metaphysics: its proponents assume that (...)
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  44. The Language of Thought: A New Philosophical Direction, by Susan Schneider.Mark Sprevak - 2019 - Mind 128 (510):555-564.
    The Language of Thought: A New Philosophical Direction, by SchneiderSusan. Cambridge, MA: MIT Press, 2011. Pp. xii + 259.
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  45. Reseña de ' Los Límites Exteriores de la Razón '(The Outer Limits of Reason) por Noson Yanofsky 403p (2013) (revision revisada 2019).Michael Richard Starks - 2019 - In Delirios Utópicos Suicidas en el Siglo 21 La filosofía, la naturaleza humana y el colapso de la civilización Artículos y reseñas 2006-2019 4a Edición. Las Vegas, NV USA: Reality Press. pp. 283-298.
    Doy una revisión detallada de ' los límites externos de la razón ' por Noson Yanofsky desde una perspectiva unificada de Wittgenstein y la psicología evolutiva. Yo indiqué que la dificultad con cuestiones como la paradoja en el lenguaje y las matemáticas, la incompletitud, la indeterminación, la computabilidad, el cerebro y el universo como ordenadores, etc., surgen de la falta de mirada cuidadosa a nuestro uso del lenguaje en el adecuado contexto y, por tanto, el Error al separar los problemas (...)
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  46. Reseña de ‘Hacer el Mundo Social’ (‘Making the Social World’) por John Searle (2010) (revisión revisada 2019).Michael Richard Starks - 2019 - In Delirios Utópicos Suicidas en el Siglo 21 La filosofía, la naturaleza humana y el colapso de la civilización Artículos y reseñas 2006-2019 4TH Edición. Las Vegas, NV USA: Reality Press. pp. 102-123.
    Antes de comentar detalladamente sobre Haciendo lo Mundo Social (MSW) primero voy a ofrecer algunos comentarios sobre la filosofía (psicología descriptiva) y su relación con la investigación psicológica contemporánea como ejemplificado en las obras de Searle (S) y Wittgenstein (W), ya que siento que esta es la mejor manera de lugar Searle o cualquier comentarista sobre el comportamiento, en la perspectiva adecuada. Será de gran ayuda para ver mis comentarios de PNC, TLP, PI, OC, TARW y otros libros de estos (...)
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  47. Será que Hominoids ou Androids Destroem a Terra? — uma revisão de Como Criar Uma Mente (How to Create a Mind) por Ray Kurzweil (2012) (revisão revisada 2019).Michael Richard Starks - 2019 - In Delírios Utópicos Suicidas no Século XXI Filosofia, Natureza Humana e o Colapso da Civilization- Artigos e Comentários 2006-2019 5ª edição. Las Vegas, NV USA: Reality Press. pp. 155-167.
    Alguns anos atrás, cheguei ao ponto onde eu normalmente pode dizer a partir do título de um livro, ou pelo menos a partir dos títulos do capítulo, que tipos de erros filosóficos serão feitas e com que freqüência. No caso de obras nominalmente científicas, estas podem ser largamente restritas a certos capítulos que enceram filosóficos ou tentam tirar conclusões gerais sobre o significado ou significado a longo prazo do trabalho. Normalmente entretanto as matérias científicas do fato são misturado generosa com (...)
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  48. ¿Los hominoides o androides destruirán la tierra? — Una revisión de ‘Cómo Crear una Mente’ (How to Create a Mind) por Ray Kurzweil (2012) (revisión revisada 2019).Michael Richard Starks - 2019 - In Delirios Utópicos Suicidas en el Siglo 21 La filosofía, la naturaleza humana y el colapso de la civilización Artículos y reseñas 2006-2019 4a Edición. Las Vegas, NV USA: Reality Press. pp. 250-262.
    Hace algunos años, Llegué al punto en el que normalmente puedo decir del título de un libro, o al menos de los títulos de los capítulos, qué tipos de errores filosóficos se harán y con qué frecuencia. En el caso de trabajos nominalmente científicos, estos pueden estar en gran parte restringidos a ciertos capítulos que enceran filosóficos o tratan de sacar conclusiones generales sobre el significado o significado a largo plazo de la obra. Normalmente, sin embargo, las cuestiones científicas de (...)
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  49. Cognition as Embodied Morphological Computation.Gordana Dodig-Crnkovic - 2018 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence 2017. Cham: Springer. pp. 19-23.
    Cognitive science is considered to be the study of mind (consciousness and thought) and intelligence in humans. Under such definition variety of unsolved/unsolvable problems appear. This article argues for a broad understanding of cognition based on empirical results from i.a. natural sciences, self-organization, artificial intelligence and artificial life, network science and neuroscience, that apart from the high level mental activities in humans, includes sub-symbolic and sub-conscious processes, such as emotions, recognizes cognition in other living beings as well as extended and (...)
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  50. The realizers and vehicles of mental representation.Zoe Drayson - 2018 - Studies in History and Philosophy of Science Part A 68:80-87.
    The neural vehicles of mental representation play an explanatory role in cognitive psychology that their realizers do not. In this paper, I argue that the individuation of realizers as vehicles of representation restricts the sorts of explanations in which they can participate. I illustrate this with reference to Rupert’s (2011) claim that representational vehicles can play an explanatory role in psychology in virtue of their quantity or proportion. I propose that such quantity-based explanatory claims can apply only to realizers and (...)
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