Results for 'Connectionism'

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  1. Connectionism, generalization, and propositional attitudes: A catalogue of challenging issues.John A. Barnden - 1992 - In J. Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum. pp. 149--178.
    [Edited from Conclusion section:] We have looked at various challenging issues to do with getting connectionism to cope with high-level cognitive activities such a reasoning and natural language understanding. The issues are to do with various facets of generalization that are not commonly noted. We have been concerned in particular with the special forms these issues take in the arena of propositional attitude processing. The main problems we have looked at are: (1) The need to construct explicit representations of (...)
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  2. 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 (...)
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  3. Connectionism and the Intentionality of the Programmer.Mark Ressler - 2003 - Dissertation, San Diego State University
    Connectionism seems to avoid many of the problems of classical artificial intelligence, but has it avoided all of them? In this thesis I examine the problem that Intentionality, the directedness of thought to an object, raises for connectionism. As a preliminary approach, I consider the role of Intentionality in classical artificial intelligence from the programmer’s point of view. In this investigation, one problem I identify with classical artificial intelligence is that the Intentionality of the programmer seems to be (...)
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  4. Language of thought: The connectionist contribution.Murat Aydede - 1997 - Minds and Machines 7 (1):57-101.
    Fodor and Pylyshyn's critique of connectionism has posed a challenge to connectionists: Adequately explain such nomological regularities as systematicity and productivity without postulating a "language of thought" (LOT). Some connectionists like Smolensky took the challenge very seriously, and attempted to meet it by developing models that were supposed to be non-classical. At the core of these attempts lies the claim that connectionist models can provide a representational system with a combinatorial syntax and processes sensitive to syntactic structure. They are (...)
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  5. The connectionist mind: A study of Hayekian psychology.Barry Smith - 1997 - In Stephen F. Frowen (ed.), Hayek: Economist and Social Philosopher: A Critical Retrospect. London: St. Martin's Press. pp. 9-29.
    In his book The Sensory Order, Hayek anticipates many of the central ideas behind what we now call the connectionist paradigm, and develops on this basis a theory of the workings of the human mind that extends the thinking of Hume and Mach. He shows that the idea of neural networks is can be applied not only in psychology and neurology but also in the sphere of economics. For the mind, from the perspective of The Sensory Order, is a dynamic, (...)
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  6. Connectionist models of mind: scales and the limits of machine imitation.Pavel Baryshnikov - 2020 - Philosophical Problems of IT and Cyberspace 2 (19):42-58.
    This paper is devoted to some generalizations of explanatory potential of connectionist approaches to theoretical problems of the philosophy of mind. Are considered both strong, and weaknesses of neural network models. Connectionism has close methodological ties with modern neurosciences and neurophilosophy. And this fact strengthens its positions, in terms of empirical naturalistic approaches. However, at the same time this direction inherits weaknesses of computational approach, and in this case all system of anticomputational critical arguments becomes applicable to the connectionst (...)
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  7. Connectionist value units: Some concerns.John A. Barnden - 1986 - Behavioral and Brain Sciences 9 (1):92-93.
    This paper is a commentary on the target article by Dana H. Ballard, “Cortical connections and parallel processing: Structure and function”, in the same issue of the journal, pp. 67–120. -/- I raise some issues about the connectionist or neural-network implementation of information and information processing. Issues include the sharing of information by different parts of a connectionist/neural network, the copying of complex information from one place to another in a network, the possibility of connection weights not being synaptic weights, (...)
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  8. Representations without Rules, Connectionism and the Syntactic Argument.Kenneth Aizawa - 1994 - Synthese 101 (3).
    This paper has a two-fold aim. First, it reinforces a version of the "syntactic argument" given in Aizawa (1994). This argument shows that connectionist networks do not provide a means of implementing representations without rules. Horgan and Tlenson have responded to the syntactic argument in their book and in another paper (Horgan & Tlenson, 1993), but their responses do not meet the challenge posed by my formulation of the syntactic argument. My second aim is to describe a kind of cognitive (...)
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  9. Chaos, symbols, and connectionism.John A. Barnden - 1987 - Behavioral and Brain Sciences 10 (2):174-175.
    The paper is a commentary on the target article by Christine A. Skarda & Walter J. Freeman, “How brains make chaos in order to make sense of the world”, in the same issue of the journal, pp.161–195. -/- I confine my comments largely to some philosophical claims that Skarda & Freeman make and to the relationship of their model to connectionism. Some of the comments hinge on what symbols are and how they might sit in neural systems.
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  10. Philosophy and Memory Traces: Descartes to Connectionism.John Sutton - 1998 - New York: Cambridge University Press.
    Philosophy and Memory Traces defends two theories of autobiographical memory. One is a bewildering historical view of memories as dynamic patterns in fleeting animal spirits, nervous fluids which rummaged through the pores of brain and body. The other is new connectionism, in which memories are 'stored' only superpositionally, and reconstructed rather than reproduced. Both models, argues John Sutton, depart from static archival metaphors by employing distributed representation, which brings interference and confusion between memory traces. Both raise urgent issues about (...)
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  11. Mind: A Connectionist Model.Nath Rajakishore - 2004 - Journal of the Indian Council of Philosophical Research 21 (3-4):43-62.
    In cognitive science, there are many computational theories regarding the function of the mind; connectionism is one of them. Connectionist networks are intricate systems of simple units related to their environment. Some have thousands of units, but those with only a few units can also behave with surprising complexity and subtlety. This is because processing occurs in parallel as also interactively, in marked contrast with the serial processing to which this is accustomed. In the first section of this paper, (...)
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  12. Your red isn't my red! Connectionist Structuralism and the puzzle of abstract objects (draft).Chris Percy - manuscript
    This draft preprint presents a nine step argument for “Connectionist Structuralism” (CS), an account of the ontology of abstract objects that is neither purely nominalist nor purely platonist. CS is a common, often implicit assumption in parts of the artificial intelligence literature, but such discussions have not presented formal accounts of the position or engaged with metaphysical issues that potentially undermine it. By making the position legible and presenting an initial case for it, we hope to support a constructive dialogue (...)
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  13. Who's afraid of multiple realizability?: Functionalism, reductionism, and connectionism.Justin Schwartz - 1992 - In J. Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum.
    Philosophers have argued that on the prevailing theory of mind, functionalism, the fact that mental states are multiply realizable or can be instantiated in a variety of different physical forms, at least in principle, shows that materialism or physical is probably false. A similar argument rejects the relevance to psychology of connectionism, which holds that mental states are embodied and and constituted by connectionist neural networks. These arguments, I argue, fall before reductios ad absurdam, proving too much -- they (...)
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  14. Folk Psychology, Eliminativism, and the Present State of Connectionism.Vanja Subotić - 2021 - Theoria: Beograd 1 (64):173-196.
    Three decades ago, William Ramsey, Steven Stich & Joseph Garon put forward an argument in favor of the following conditional: if connectionist models that implement parallelly distributed processing represent faithfully human cognitive processing, eliminativism about propositional attitudes is true. The corollary of their argument (if it proves to be sound) is that there is no place for folk psychology in contemporary cognitive science. This understanding of connectionism as a hypothesis about cognitive architecture compatible with eliminativism is also endorsed by (...)
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  15. Logical Reasoning and Expertise: Extolling the Virtues of Connectionist Account of Enthymemes.Vanja Subotić - 2021 - Filozofska Istrazivanja 1 (161):197-211.
    Cognitive scientists used to deem reasoning either as a higher cognitive process based on the manipulation of abstract rules or as a higher cognitive process that is stochastic rather than involving abstract rules. I maintain that these different perspectives are closely intertwined with a theoretical and methodological endorsement of either cognitivism or connectionism. Cognitivism and connectionism represent two prevailing and opposed paradigms in cognitive science. I aim to extoll the virtues of connectionist models of enthymematic reasoning by following (...)
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  16. Reduction and levels of explanation in connectionism.John Sutton - 1995 - In P. Slezak, T. Caelli & R. Clark (eds.), Perspectives on cognitive science: theories, experiments, and foundations. Ablex. pp. 347-368.
    Recent work in the methodology of connectionist explanation has I'ocrrsccl on the notion of levels of explanation. Specific issucs in conncctionisrn hcrc intersect with rvider areas of debate in the philosophy of psychology and thc philosophy of science generally. The issues I raise in this chapter, then, are not unique to cognitive science; but they arise in new and important contexts when connectionism is taken seriously as a model of cognition. The general questions are the relation between levels and (...)
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  17. Filling the Gaps: Hume and Connectionism on the Continued Existence of Unperceived Objects.Mark Collier - 1999 - Hume Studies 25 (1 and 2):155-170.
    In Book I, part iv, section 2 of the Treatise, "Of scepticism with regard to the senses," Hume presents two different answers to the question of how we come to believe in the continued existence of unperceived objects. He rejects his first answer shortly after its formulation, and the remainder of the section articulates an alternative account of the development of the belief. The account that Hume adopts, however, is susceptible to a number of insurmountable objections, which motivates a reassessment (...)
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  18. Empiricism without Magic: Transformational Abstraction in Deep Convolutional Neural Networks.Cameron Buckner - 2018 - Synthese (12):1-34.
    In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often appealing to (...)
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  19. The Exploratory Status of Postconnectionist Models.Miljana Milojevic & Vanja Subotić - 2020 - Theoria: Beograd 2 (63):135-164.
    This paper aims to offer a new view of the role of connectionist models in the study of human cognition through the conceptualization of the history of connectionism – from the simplest perceptrons to convolutional neural nets based on deep learning techniques, as well as through the interpretation of criticism coming from symbolic cognitive science. Namely, the connectionist approach in cognitive science was the target of sharp criticism from the symbolists, which on several occasions caused its marginalization and almost (...)
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  20. Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines.Gordana Dodig-Crnkovic - 2020 - Philosophies 5 (3):17.
    The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what at (...)
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  21. On Paul Cilliers’ approach to complexity: Post-structuralism versus model exclusivity.Ragnar Van Der Merwe - 2021 - INDECS: Interdisciplinary Description of Complex Systems 19 (4):457-469.
    Paul Cilliers has developed a novel post-structural approach to complexity that has influenced several writers contributing to the current complexity literature. Concomitantly however, Cilliers advocates for modelling complex systems using connectionist neural networks (rather than analytic, rule-based models). In this paper, I argue that it is dilemmic to simultaneously hold these two positions. Cilliers’ post-structural interpretation of complexity states that models of complex systems are always contextual and provisional; there is no exclusive model of complex systems. This sentiment however appears (...)
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  22. Rules in programming languages and networks.Frederick R. Adams, Kenneth Aizawa & Gary Fuller - 1992 - In J. Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum.
    1. Do models formulated in programming languages use explicit rules where connectionist models do not? 2. Are rules as found in programming languages hard, precise, and exceptionless, where connectionist rules are not? 3. Do connectionist models use rules operating on distributed representations where models formulated in programming languages do not? 4. Do connectionist models fail to use structure sensitive rules of the sort found in "classical" computer architectures? In this chapter we argue that the answer to each of these questions (...)
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  23. Eliminativism and Reading One's Own Mind.T. Parent - manuscript
    Some contemporary philosophers suggest that we know just by introspection that folk psychological states exist. However, such an "armchair refutation" of eliminativism seems too easy. I first attack two strategems, inspired by Descartes, on how such a refutation might proceed. However, I concede that the Cartesian intuition that we have direct knowledge of representational states is very powerful. The rest of this paper then offers an error theory of how that intuition might really be mistaken. The idea is that introspection (...)
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  24. The Discovery of the Artificial: Behavior, Mind and Machines Before and Beyond Cybernetics.Roberto Cordeschi - 2002 - Kluwer Academic Publishers.
    Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building (...)
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  25. Systematicity and Conceptual Pluralism.Fernando Martinez-Manrique - 2014 - In Paco Calvo John Symons (ed.), The Architecture of Cognition: Rethinking Fodor and Pylyshyn's Systematicity Challenge. MIT Press. pp. 305-334.
    The systematicity argument only challenges connectionism if systematicity is a general property of cognition. I examine this thesis in terms of properties of concepts. First, I propose that Evans's Generality Constraint only applies to attributions of belief. Then I defend a variety of conceptual pluralism, arguing that concepts share two fundamental properties related to centrality and belief-attribution, and contending that there are two kinds of concepts that differ in their compositional properties. Finally, I rely on Dual Systems Theory and (...)
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  26. Time phases, pointers, rules and embedding.John A. Barnden - 1993 - Behavioral and Brain Sciences 16 (3):451-452.
    This paper is a commentary on the target article by Lokendra Shastri & Venkat Ajjanagadde [S&A]: “From simple associations to systematic reasoning: A connectionist representation of rules, variables and dynamic bindings using temporal synchrony” in same issue of the journal, pp.417–451. -/- It puts S&A's temporal-synchrony binding method in a broader context, comments on notions of pointing and other ways of associating information - in both computers and connectionist systems - and mentions types of reasoning that are a challenge to (...)
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  27. The centrality of instantiations.John A. Barnden - 1987 - Behavioral and Brain Sciences 10 (3):437-438.
    This paper is a commentary on the target article by Michael Arbib, “Levels of modeling of mechanisms of visually guided behavior”, in the same issue of the journal, pp. 407–465. -/- I focus on the importance of the inclusion of an ability of a system to entertain, at a given time, multiple instantiations of a given schema (situation template, frame, script, action plan, etc.), and complications introduced into neural/connectionist network systems by such inclusion.
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  28. A critique of the causal theory of memory.Marina Trakas - 2010 - Dissertation, Ecole des Hautes Etudes En Sciences Sociales
    In this Master's dissertation, I try to show that the causal theory of memory, which is the only theory developed so far that at first view seems more plausible and that could be integrated with psychological explanations and investigations of memory, shows some conceptual and ontological problems that go beyond the internal inconsistencies that each version can present. On one hand, the memory phenomenon analyzed is very limited: in general it is reduced to the conscious act of remembering expressed in (...)
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  29. Linguistic Competence and New Empiricism in Philosophy and Science.Vanja Subotić - 2023 - Dissertation, University of Belgrade
    The topic of this dissertation is the nature of linguistic competence, the capacity to understand and produce sentences of natural language. I defend the empiricist account of linguistic competence embedded in the connectionist cognitive science. This strand of cognitive science has been opposed to the traditional symbolic cognitive science, coupled with transformational-generative grammar, which was committed to nativism due to the view that human cognition, including language capacity, should be construed in terms of symbolic representations and hardwired rules. Similarly, linguistic (...)
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  30. A Deflationary Account of Mental Representation.Frances Egan - 2020 - In Joulia Smortchkova, Krzysztof Dołrega & Tobias Schlicht (eds.), What Are Mental Representations? New York, NY, United States of America: Oxford University Press.
    Among the cognitive capacities of evolved creatures is the capacity to represent. Theories in cognitive neuroscience typically explain our manifest representational capacities by positing internal representations, but there is little agreement about how these representations function, especially with the relatively recent proliferation of connectionist, dynamical, embodied, and enactive approaches to cognition. In this talk I sketch an account of the nature and function of representation in cognitive neuroscience that couples a realist construal of representational vehicles with a pragmatic account of (...)
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  31. The Bodily Basis of Thought.Jay Seitz - 2000 - New Ideas in Psychology 18 (1):23-40.
    Classical cognitivist and connectionist models posit a Cartesian disembodiment of mind assuming that brain events can adequately explain thought and related notions such as intellect. Instead, we argue for the bodily basis of thought and its continuity beyond the sensorimotor stage. Indeed, there are no eternally fixed representations of the external world in the "motor system," rather, it is under the guidance of both internal and external factors with important linkages to frontal, parietal, cerebellar, basal ganglionic, and cingulate gyrus areas (...)
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  32. The computational and the representational language-of-thought hypotheses.David J. Chalmers - 2023 - Behavioral and Brain Sciences 46:e269.
    There are two versions of the language-of-thought hypothesis (LOT): Representational LOT (roughly, structured representation), introduced by Ockham, and computational LOT (roughly, symbolic computation) introduced by Fodor. Like many others, I oppose the latter but not the former. Quilty-Dunn et al. defend representational LOT, but they do not defend the strong computational LOT thesis central to the classical-connectionist debate.
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  33. Artificial virtuous agents: from theory to machine implementation.Jakob Stenseke - 2021 - AI and Society:1-20.
    Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, we (...)
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  34. Book: Cognitive Design for Artificial Minds.Antonio Lieto - 2021 - London, UK: Routledge, Taylor & Francis Ltd.
    Book Description (Blurb): Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. -/- Beginning with an overview of the historical, methodological and technical issues in the field of Cognitively-Inspired Artificial Intelligence, (...)
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  35. Natural morphological computation as foundation of learning to learn in humans, other living organisms, and intelligent machines.Gordana Dodig-Crnkovic - 2020 - Philosophies 5 (3):17-32.
    The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...)
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  36. Conceptual Spaces for Cognitive Architectures: A Lingua Franca for Different Levels of Representation.Antonio Lieto, Antonio Chella & Marcello Frixione - 2017 - Biologically Inspired Cognitive Architectures 19:1-9.
    During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [35]) adopt a classical symbolic approach, some (e.g. LEABRA[ 48]) are based on a purely connectionist model, while others (e.g. CLARION [59]) adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and reasoning are (...)
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  37. Putting a Price on Cognition.David Kirsh - 1988 - Southern Journal of Philosophy 26 (S1):119-135.
    In this essay I shall consider a certain methodological claim gaining currency in connectionist quarters: The claim that variables are costly to implement in PDP systems and hence are not likely to be as important in cognitive processing as orthodox theories of cognition assume.
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  38. The Structure of Sensorimotor Explanation.Alfredo Vernazzani - 2018 - Synthese (11):4527-4553.
    The sensorimotor theory of vision and visual consciousness is often described as a radical alternative to the computational and connectionist orthodoxy in the study of visual perception. However, it is far from clear whether the theory represents a significant departure from orthodox approaches or whether it is an enrichment of it. In this study, I tackle this issue by focusing on the explanatory structure of the sensorimotor theory. I argue that the standard formulation of the theory subscribes to the same (...)
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  39. Representations gone mental.Alex Morgan - 2014 - Synthese 191 (2):213-244.
    Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of (...)
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  40. Computers, Dynamical Systems, Phenomena, and the Mind.Marco Giunti - 1992 - Dissertation, Indiana University
    This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of dynamical systems, which I (...)
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  41. Cognitive Ecology as a Framework for Shakespearean Studies.Evelyn Tribble & John Sutton - 2011 - Shakespeare Studies 39:94-103.
    ‘‘COGNITIVE ECOLOGY’’ is a fruitful model for Shakespearian studies, early modern literary and cultural history, and theatrical history more widely. Cognitive ecologies are the multidimensional contexts in which we remember, feel, think, sense, communicate, imagine, and act, often collaboratively, on the fly, and in rich ongoing interaction with our environments. Along with the anthropologist Edwin Hutchins,1 we use the term ‘‘cognitive ecology’’ to integrate a number of recent approaches to cultural cognition: we believe these approaches offer productive lines of engagement (...)
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  42. 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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  43. Dynamic Cognition Applied to Value Learning in Artificial Intelligence.Nythamar De Oliveira & Nicholas Corrêa - 2021 - Aoristo - International Journal of Phenomenology, Hermeneutics and Metaphysics 4 (2):185-199.
    Experts in Artificial Intelligence (AI) development predict that advances in the dvelopment of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance isn't done with prudence, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of artificial intelligence. Currently, several of the open problems in the field of AI research arise from the difficulty of avoiding unwanted (...)
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  44. Computationalism under attack.Roberto Cordeschi & Marcello Frixione - 2007 - In M. Marraffa, M. De Caro & F. Ferretti (eds.), Cartographies of the Mind: Philosophy and Psychology in Intersection. Springer.
    Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and aims. Zenon (...)
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  45. AI, alignment, and the categorical imperative.Fritz McDonald - 2023 - AI and Ethics 3:337-344.
    Tae Wan Kim, John Hooker, and Thomas Donaldson make an attempt, in recent articles, to solve the alignment problem. As they define the alignment problem, it is the issue of how to give AI systems moral intelligence. They contend that one might program machines with a version of Kantian ethics cast in deontic modal logic. On their view, machines can be aligned with human values if such machines obey principles of universalization and autonomy, as well as a deontic utilitarian principle. (...)
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  46. Brand Equity Planning with Structuralist Rhetorical Semiotics.George Rossolatos - 2014 - Kassel: Kassel University Press.
    Brand Equity Planning with Structuralist Rhetorical Semiotics furnishes an innovative conceptual model and methodology for brand equity planning, with view to addressing a crucial gap in the marketing and semiotic literatures concerning how advertising multimodal textual elements may be transformed into brand associations, with an emphasis on rhetorical relata as modes of connectivity between a brand’s surface and depth grammar. The scope of this project is inter-disciplinary, spanning research areas such as brand equity, structuralist semiotics, textual semiotics, visual and film (...)
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  47. Turning Negative Causation Back to Positive.Peter Fazekas & George Kampis - manuscript
    In contemporary literature, the fact that there is negative causation is the primary motivation for rejecting the physical connection view, and arguing for alternative accounts of causation. In this paper we insist that such a conclusion is too fast. We present two frameworks, which help the proponent of the physical connection view to resist the anti-connectionist conclusion. According to the first framework, there are positive causal claims, which co-refer with at least some negative causal claims. According to the second framework, (...)
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  48. La modellizzazione computazionale della competenza inferen-ziale e della competenza referenziale.Fabrizio Calzavarini & Antonio Lieto - forthcoming - Sistemi Intelligenti.
    In philosophy of language, a distinction has been proposed by Diego Marconi between two aspects of lexical competence, i.e. referential and inferential competence. The former accounts for the relation-ship of words to the world, the latter for the relationship of words among themselves. The aim of the pa-per is to offer a critical discussion of the kind of formalisms and computational techniques that can be used in Artificial Intelligence to model the two aspects of lexical competence, and of the main (...)
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  49. Distributed traces and the causal theory of constructive memory.John Sutton & Gerard O'Brien - 2023 - In John Sutton & Gerard O'Brien (eds.), Current Controversies in the Philosophy of Memory. Routledge. pp. 82-104. Translated by Andre Sant' Anna, Christopher McCarroll & Kourken Michaelian.
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  50. A Unified Cognitive Model of Visual Filling-In Based on an Emergic Network Architecture.David Pierre Leibovitz - 2013 - Dissertation, Carleton University
    The Emergic Cognitive Model (ECM) is a unified computational model of visual filling-in based on the Emergic Network architecture. The Emergic Network was designed to help realize systems undergoing continuous change. In this thesis, eight different filling-in phenomena are demonstrated under a regime of continuous eye movement (and under static eye conditions as well). -/- ECM indirectly demonstrates the power of unification inherent with Emergic Networks when cognition is decomposed according to finer-grained functions supporting change. These can interact to raise (...)
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