Search results for 'physical symbol system hypothesis' (try it on Scholar)

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  1. Andrew Wells (1996). Situated Action, Symbol Systems and Universal Computation. Minds and Machines 6 (1):33-46.score: 280.0
    Vera & Simon (1993a) have argued that the theories and methods known as situated action or situativity theory are compatible with the assumptions and methodology of the physical symbol systems hypothesis and do not require a new approach to the study of cognition. When the central criterion of computational universality is added to the loose definition of a symbol system which Vera and Simon provide, it becomes apparent that there are important incompatibilities between the two (...)
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  2. Graham White (2011). Descartes Among the Robots. Minds and Machines 21 (2):179-202.score: 263.3
    We consider the symbol grounding problem, and apply to it philosophical arguments against Cartesianism developed by Sellars and McDowell: the problematic issue is the dichotomy between inside and outside which the definition of a physical symbol system presupposes. Surprisingly, one can question this dichotomy and still do symbolic computation: a detailed examination of the hardware and software of serial ports shows this.
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  3. Peter beim Graben (2004). Incompatible Implementations of Physical Symbol Systems. Mind and Matter 2 (2):29-51.score: 249.8
    Classical cognitive science assumes that intelligently behaving systems must be symbol processors that are implemented in physical systems such as brains or digital computers. By contrast, connectionists suppose that symbol manipulating systems could be approximations of neural networks dynamics. Both classicists and connectionists argue that symbolic computation and subsymbolic dynamics are incompatible, though on different grounds. While classicists say that connectionist architectures and symbol processors are either incompatible or the former are mere implementations of the latter, (...)
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  4. Kathryn Blackmond Laskey (2014). Information, Physics and the Representing Mind. Cosmos and History: The Journal of Natural and Social Philosophy 10 (1):131-139.score: 220.5
    A primary function of mind is to form and manipulate representations to identify and choose survival-enhancing behaviors. Representations are themselves physical systems that can be manipulated to reason about, predict, or plan actions involving the objects they designate. The field of knowledge representation and reasoning (KRR) turns representation upon itself to study how representations are formed and used by biological and computer systems. Some of the most versatile and successful KRR methods have been imported from computational physics. Features of (...)
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  5. Christopher Viger (2007). The Acquired Language of Thought Hypothesis. Interaction Studies 8 (1):125-142.score: 216.0
    I present the symbol grounding problem in the larger context of a materialist theory of content and then present two problems for causal, teleo-functional accounts of content. This leads to a distinction between two kinds of mental representations: presentations and symbols; only the latter are cognitive. Based on Milner and Goodale’s dual route model of vision, I posit the existence of precise interfaces between cognitive systems that are activated during object recognition. Interfaces are constructed as a child learns, and (...)
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  6. Roberto Cordeschi & Marcello Frixione (2007). Computationalism Under Attack. In M. Marraffa, M. De Caro & F. Ferretti (eds.), Cartographies of the Mind: Philosophy and Psychology in Intersection. Springer.score: 212.0
    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 (...)
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  7. Hubert L. Dreyfus (1988). The Socratic and Platonic Basis of Cognitivism. AI and Society 2 (2):99-112.score: 175.5
    Artificial Intelligence, and the cognitivist view of mind on which it is based, represent the last stage of the rationalist tradition in philosophy. This tradition begins when Socrates assumes that intelligence is based on principles and when Plato adds the requirement that these principles must be strict rules, not based on taken-for-granted background understanding. This philosophical position, refined by Hobbes, Descartes and Leibniz, is finally converted into a research program by Herbert Simon and Allen Newell. That research program is now (...)
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  8. Chris Moss (1989). Artificial Intelligence and Symbols. AI and Society 3 (4):345-356.score: 171.0
    The introduction of massive parallelism and the renewed interest in neural networks gives a new need to evaluate the relationship of symbolic processing and artificial intelligence. The physical symbol hypothesis has encountered many difficulties coping with human concepts and common sense. Expert systems are showing more promise for the early stages of learning than for real expertise. There is a need to evaluate more fully the inherent limitations of symbol systems and the potential for programming compared (...)
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  9. David Lumsden (2005). How Can a Symbol System Come Into Being? Dialogue 44 (1):87-96.score: 162.0
    One holistic thesis about symbols is that a symbol cannot exist singly, but only as apart of a symbol system. There is also the plausible view that symbol systems emerge gradually in an individual, in a group, and in a species. The problem is that symbol holism makes it hard to see how a symbol system can emerge gradually, at least if we are considering the emergence of a first symbol system. (...)
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  10. Kathryn Blackmond Laskey (2006). Quantum Physical Symbol Systems. Journal of Logic, Language and Information 15 (1-2):109-154.score: 157.8
    Because intelligent agents employ physically embodied cognitive systems to reason about the world, their cognitive abilities are constrained by the laws of physics. Scientists have used digital computers to develop and validate theories of physically embodied cognition. Computational theories of intelligence have advanced our understanding of the nature of intelligence and have yielded practically useful systems exhibiting some degree of intelligence. However, the view of cognition as algorithms running on digital computers rests on implicit assumptions about the physical world (...)
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  11. Nick Braisby, Richard Cooper & Bradley Franks (1998). Why the Dynamical Hypothesis Cannot Qualify as a Law of Qualitative Structure. Behavioral and Brain Sciences 21 (5):630-631.score: 156.5
    Van Gelder presents the dynamical hypothesis as a novel law of qualitative structure to compete with Newell and Simon's (1976) physical symbol systems hypothesis. Unlike Newell and Simon's hypothesis, the dynamical hypothesis fails to provide necessary and sufficient conditions for cognition. Furthermore, imprecision in the statement of the dynamical hypothesis renders it unfalsifiable.
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  12. Angelo Cangelosi, Alberto Greco & Stevan Harnad (2002). Symbol Grounding and the Symbolic Theft Hypothesis. In A. Cangelosi & D. Parisi (eds.), Simulating the Evolution of Language. Springer-Verlag. 191--210.score: 153.0
    Scholars studying the origins and evolution of language are also interested in the general issue of the evolution of cognition. Language is not an isolated capability of the individual, but has intrinsic relationships with many other behavioral, cognitive, and social abilities. By understanding the mechanisms underlying the evolution of linguistic abilities, it is possible to understand the evolution of cognitive abilities. Cognitivism, one of the current approaches in psychology and cognitive science, proposes that symbol systems capture mental phenomena, and (...)
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  13. Allen Newell (1980). Physical Symbol Systems. Cognitive Science 4 (2):135-83.score: 141.8
  14. Vinod Goel (1991). Notationality and the Information Processing Mind. Minds and Machines 1 (2):129-166.score: 141.8
    Cognitive science uses the notion of computational information processing to explain cognitive information processing. Some philosophers have argued that anything can be described as doing computational information processing; if so, it is a vacuous notion for explanatory purposes.An attempt is made to explicate the notions of cognitive information processing and computational information processing and to specify the relationship between them. It is demonstrated that the resulting notion of computational information processing can only be realized in a restrictive class of dynamical (...)
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  15. David S. Touretzky & Dean A. Pomerleau (1994). Reconstructing Physical Symbol Systems. Cognitive Science 18 (2):345-353.score: 141.8
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  16. K. Laskey (forthcoming). Quantum Physical Symbol Systems. Submitted to Special Issue Of. Minds and Machines.score: 141.8
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  17. Alonso H. Vera & Herbert A. Simon (1994). Reply to Touretzky and Pomerleau: Reconstructing Physical Symbol Systems. Cognitive Science 18 (2):355-360.score: 141.8
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  18. Louis C. Charland (1999). Perceptual Symbol Systems and Emotion. Behavioral and Brain Sciences 22 (4):612-613.score: 141.0
    In his target article, Barsalou cites current work on emotion theory but does not explore its relevance for this project. The connection is worth pursuing, since there is a plausible case to be made that emotions form a distinct symbolic information processing system of their own. On some views, that system is argued to be perceptual: a direct connection with Barsalou's perceptual symbol systems theory. Also relevant is the hypothesis that there may be different modular subsystems (...)
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  19. Debasis Patnaik (forthcoming). Theorizing Change in Artificial Intelligence: Inductivising Philosophy From Economic Cognition Processes. [REVIEW] AI and Society:1-9.score: 121.5
    Economic value additions to knowledge and demand provide practical, embedded and extensible meaning to philosophizing cognitive systems. Evaluation of a cognitive system is an empirical matter. Thinking of science in terms of distributed cognition (interactionism) enlarges the domain of cognition. Anything that actually contributes to the specific quality of output of a cognitive system is part of the system in time and/or space. Cognitive science studies behaviour and knowledge structures of experts and categorized structures based on underlying (...)
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  20. W. R. Ashby (1947). The Nervous System as Physical Machine: With Special Reference to the Origin of Adaptive Behaviour. Mind 56 (January):44-59.score: 120.0
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  21. H. H. Pattee (2013). Epistemic, Evolutionary, and Physical Conditions for Biological Information. Biosemiotics 6 (1):9-31.score: 120.0
    The necessary but not sufficient conditions for biological informational concepts like signs, symbols, memories, instructions, and messages are (1) an object or referent that the information is about, (2) a physical embodiment or vehicle that stands for what the information is about (the object), and (3) an interpreter or agent that separates the referent information from the vehicle’s material structure, and that establishes the stands-for relation. This separation is named the epistemic cut, and explaining clearly how the stands-for relation (...)
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  22. David L. Katz, Kerem Shuval, Beth P. Comerford, Zubaida Faridi & Valentine Y. Njike (2008). Impact of an Educational Intervention on Internal Medicine Residents' Physical Activity Counselling: The Pressure System Model. Journal of Evaluation in Clinical Practice 14 (2):294-299.score: 120.0
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  23. Josefa Toribio, Efficacy, Content and Levels of Explanation.score: 118.0
    Let’s consider the following paradox (Fodor [1989], Jackson and Petit [1988] [1992], Drestke [1988], Block [1991], Lepore and Loewer [1987], Lewis [1986], Segal and Sober [1991]): i) The intentional content of a thought (or any other intentional state) is causally relevant to its behavioural (and other) effects. ii) Intentional content is nothing but the meaning of internal representations. But, iii) Internal processors are only sensitive to the syntactic structures of internal representations, not their meanings. Therefore it seems that if we (...)
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  24. Evan Thompson (1997). Symbol Grounding: A Bridge From Artificial Life to Artificial Intelligence. Brain and Cognition 34 (1):48-71.score: 112.5
    This paper develops a bridge from AL issues about the symbol–matter relation to AI issues about symbol-grounding by focusing on the concepts of formality and syntactic interpretability. Using the DNA triplet-amino acid specification relation as a paradigm, it is argued that syntactic properties can be grounded as high-level features of the non-syntactic interactions in a physical dynamical system. This argu- ment provides the basis for a rebuttal of John Searle’s recent assertion that syntax is observer-relative (1990, (...)
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  25. Andrew A. Fingelkurts, Alexander A. Fingelkurts & Carlos F. H. Neves (2010). Natural World Physical, Brain Operational, and Mind Phenomenal Space-Time. Physics of Life Reviews 7 (2):195-249.score: 111.0
    Concepts of space and time are widely developed in physics. However, there is a considerable lack of biologically plausible theoretical frameworks that can demonstrate how space and time dimensions are implemented in the activity of the most complex life-system – the brain with a mind. Brain activity is organized both temporally and spatially, thus representing space-time in the brain. Critical analysis of recent research on the space-time organization of the brain’s activity pointed to the existence of so-called operational space-time (...)
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  26. Harri Veivo (2012). The City as a Mediating Device and as a Symbol in Finnish Poetry of the 1960s. Sign Systems Studies 40 (3-4):514-527.score: 111.0
    In Finnish poetry of the 1960s, the city, and above all the capital Helsinki, is the scene where the metamorphosis of Finland from an agrarian into an urban society is staged, analysed and commented. It is also a symbol that serves to situate the country in the global context, with all the contradictions that were characteristic of the position of Finland in the cold war system. Writing about the city was a means to reflect on the transformations of (...)
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  27. Lawrence W. Barsalou (1999). Perceptual Symbol Systems. Behavioral and Brain Sciences 22 (4):577-660.score: 109.5
    Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...)
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  28. Marton Gomori & Laszlo E. Szabo, Is the Relativity Principle Consistent with Electrodynamics? Towards a Logico-Empiricist Reconstruction of a Physical Theory.score: 108.0
    It is common in the literature on electrodynamics and relativity theory that the transformation rules for the basic electrodynamical quantities are derived from the hypothesis that the relativity principle (RP) applies for Maxwell's electrodynamics. As it will turn out from our analysis, these derivations raise several problems, and certain steps are logically questionable. This is, however, not our main concern in this paper. Even if these derivations were completely correct, they leave open the following questions: (1) Is (RP) a (...)
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  29. David Pitt, The Paraphenomenal Hypothesis.score: 108.0
    Gilbert Ryle accused Descartes of advancing what he called the “paramechanical hypothesis,” according to which the structure and operations of the mind can be understood on the model of the structure and operations of a physical system. The body is a complex machine – “a bit of clockwork” – that operates according to laws governing the mechanical interactions of material things. The mind, on the other hand, according to Descartes (according to Ryle), is an immaterial machine that (...)
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  30. Michael A. Arbib (2005). The Mirror System Hypothesis Stands but the Framework is Much Enriched. Behavioral and Brain Sciences 28 (2):149-159.score: 108.0
    Challenges for extending the mirror system hypothesis include mechanisms supporting planning, conversation, motivation, theory of mind, and prosody. Modeling remains relevant. Co-speech gestures show how manual gesture and speech intertwine, but more attention is needed to the auditory system and phonology. The holophrastic view of protolanguage is debated, along with semantics and the cultural basis of grammars. Anatomically separated regions may share an evolutionary history.
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  31. W. Tecumseh Fitch & Marc D. Hauser (1998). Differences That Make a Difference: Do Locus Equations Result From Physical Principles Characterizing All Mammalian Vocal Tracts? Behavioral and Brain Sciences 21 (2):264-265.score: 108.0
    Sussman and colleagues provide no evidence supporting their claim that the human vocal production system is specialized to produce locus equations with high correlations and linearity. We propose the alternative null hypothesis that these features result from physical and physiological factors common to all mammalian vocal tracts and we recommend caution in assuming that human speech production mechanisms are unique.
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  32. Stevan Harnad (1992). Virtual Symposium on Virtual Mind. Minds and Machines 2 (3):217-238.score: 104.3
    When certain formal symbol systems (e.g., computer programs) are implemented as dynamic physical symbol systems (e.g., when they are run on a computer) their activity can be interpreted at higher levels (e.g., binary code can be interpreted as LISP, LISP code can be interpreted as English, and English can be interpreted as a meaninguful conversation). These higher levels of interpretability are called ‘virtual’ systems. If such a virtual system is interpretable as if it had a mind, (...)
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  33. Tim van Gelder (1999). Defending the Dynamic Hypothesis. In Wolfgang Tschacher & J-P Dauwalder (eds.), Dynamics, Synergetics, Autonomous Agents: Nonlinear Systems Approaches to Cognitive Psychology and Cognitive Science. Singapore: World Scientific.score: 100.0
    Cognitive science has always been dominated by the idea that cognition is _computational _in a rather strong and clear sense. Within the mainstream approach, cognitive agents are taken to be what are variously known as _physical symbol_ _systems, digital computers_, _syntactic engines_, or_ symbol manipulators_. Cognitive operations are taken to consist in the shuffling of symbol tokens according to strict rules (programs). Models of cognition are themselves digital computers, implemented on general purpose electronic machines. The basic mathematical framework (...)
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  34. Gilberto Gomes (1995). Self-Awareness and the Mind-Brain Problem. Philosophical Psychology 8 (2):155-65.score: 99.0
    The prima facie heterogeneity between psychical and physical phenomena seems to be a serious objection to psychoneural identity thesis, according to many authors, from Leibniz to Popper. It is argued that this objection can be superseded by a different conception of consciousness. Consciousness, while being conscious of something, is always unconscious of itself . Consciousness of being conscious is not immediate, it involves another, second-order, conscious state. The appearance of mental states to second-order consciousness does not reveal their true (...)
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  35. Paul Busch & Pekka J. Lahti (1989). The Determination of the Past and the Future of a Physical System in Quantum Mechanics. Foundations of Physics 19 (6):633-678.score: 98.0
    The determination of the past and the future of a physical system are complementary aims of measurements. An optimal determination of the past of a system can be achieved by an informationally complete set of physical quantities. Such a set is always strongly noncommutative. An optimal determination of the future of a physical system can be obtained by a Boolean complete set of quantities. The two aims can be reconciled to a reasonable degree with (...)
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  36. Margaret A. Boden (1970). Intentionality and Physical Systems. Philosophy of Science 32 (June):200-214.score: 96.0
    Intentionality is characteristic of many psychological phenomena. It is commonly held by philosophers that intentionality cannot be ascribed to purely physical systems. This view does not merely deny that psychological language can be reduced to physiological language. It also claims that the appropriateness of some psychological explanation excludes the possibility of any underlying physiological or causal account adequate to explain intentional behavior. This is a thesis which I do not accept. I shall argue that physical systems of a (...)
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  37. Nir Fresco (2011). Concrete Digital Computation: What Does It Take for a Physical System to Compute? [REVIEW] Journal of Logic, Language and Information 20 (4):513-537.score: 96.0
    This paper deals with the question: what are the key requirements for a physical system to perform digital computation? Time and again cognitive scientists are quick to employ the notion of computation simpliciter when asserting basically that cognitive activities are computational. They employ this notion as if there was or is a consensus on just what it takes for a physical system to perform computation, and in particular digital computation. Some cognitive scientists in referring to digital (...)
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  38. Angelo Loula, Ricardo Gudwin, Charbel El-Hani & João Queiroz, The Emergence of Symbol-Based Communication in a Complex System of Artificial Creatures.score: 96.0
    We present here a digital scenario to simulate the emergence of self-organized symbol-based communication among artificial creatures inhabiting a virtual world of predatory events. In order to design the environment and creatures, we seek theoretical and empirical constraints from C.S.Peirce Semiotics and an ethological case study of communication among animals. Our results show that the creatures, assuming the role of sign users and learners, behave collectively as a complex system, where self-organization of communicative interactions plays a major role (...)
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  39. V. K. Jirsa & J. A. S. Kelso (2000). Beyond the Limits of the Brain as a Physical System. Behavioral and Brain Sciences 23 (3):405-406.score: 96.0
    Nunez's description of the brain as a medium capable of wave propagation has provided some fundamental insights into its dynamics. This approach soon reaches the descriptive limits of the brain as a physical system, however. We point out some biological constraints which differentiate the brain from physical systems and we elaborate on its consequences for future research.
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  40. John Dempsher (1980). A Bio-Physical Basis of Mathematics in Synaptic Function of the Nervous System: A Theory. Acta Biotheoretica 29 (3-4).score: 96.0
    The purpose of this paper is to present a bio-physical basis of mathematics. The essence of the theory is that function in the nervous system is mathematical. The mathematics arises as a result of the interaction of energy (a wave with a precise curvature in space and time) and matter (a molecular or ionic structure with a precise form in space and time). In this interaction, both energy and matter play an active role. That is, the interaction results (...)
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  41. Stevan Harnad, Grounding Symbolic Capacity in Robotic Capacity.score: 94.5
    According to "computationalism" (Newell, 1980; Pylyshyn 1984; Dietrich 1990), mental states are computational states, so if one wishes to build a mind, one is actually looking for the right program to run on a digital computer. A computer program is a semantically interpretable formal symbol system consisting of rules for manipulating symbols on the basis of their shapes, which are arbitrary in relation to what they can be systematically interpreted as meaning. According to computationalism, every physical implementation (...)
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  42. Mauro Gattari (2005). Finite and Physical Modalities. Notre Dame Journal of Formal Logic 46 (4):425-437.score: 90.0
    The logic Kf of the modalities of finite, devised to capture the notion of 'there exists a finite number of accessible worlds such that . . . is true', was introduced and axiomatized by Fattorosi. In this paper we enrich the logical framework of Kf: we give consistency properties and a tableau system (which yields the decidability) explicitly designed for Kf, and we introduce a shorter and more natural axiomatization. Moreover, we show the strong and suggestive relationship between Kf (...)
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  43. Derek C. Penn, Keith J. Holyoak & Daniel J. Povinelli (2008). Darwin's Mistake: Explaining the Discontinuity Between Human and Nonhuman Minds. Behavioral and Brain Sciences 31 (2):109-130.score: 87.8
    Over the last quarter century, the dominant tendency in comparative cognitive psychology has been to emphasize the similarities between human and nonhuman minds and to downplay the differences as (Darwin 1871). In the present target article, we argue that Darwin was mistaken: the profound biological continuity between human and nonhuman animals masks an equally profound discontinuity between human and nonhuman minds. To wit, there is a significant discontinuity in the degree to which human and nonhuman animals are able to approximate (...)
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  44. William P. Bechtel (1986). What Happens to Accounts of Mind-Brain Relations If We Forgo an Architecture of Rules and Representations? Philosophy of Science Association 1986:159 - 171.score: 87.8
    The notion that the mind is a physical symbol system (Newell) with a determinate functional architecture (Pylyshyn) provides a compelling conception of the relation of cognitive inquiry to neuroscience inquiry: cognitive inquiry explores the activity within the symbol system while neuroscience explains how the symbol system is realized in the brain. However, the view the the mind is a physical symbol system is being challenged today by researchers in artificial intelligence (...)
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  45. Andy Clark (2006). Material Symbols. Philosophical Psychology 19 (3):291-307.score: 87.0
    What is the relation between the material, conventional symbol structures that we encounter in the spoken and written word, and human thought? A common assumption, that structures a wide variety of otherwise competing views, is that the way in which these material, conventional symbol-structures do their work is by being translated into some kind of content-matching inner code. One alternative to this view is the tempting but thoroughly elusive idea that we somehow think in some natural language (such (...)
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  46. Attila Grandpierre (2013). The Origin of Cellular Life and Biosemiotics. Biosemiotics (3):1-15.score: 87.0
    Recent successes of systems biology clarified that biological functionality is multilevel. We point out that this fact makes it necessary to revise popular views about macromolecular functions and distinguish between local, physico-chemical and global, biological functions. Our analysis shows that physico-chemical functions are merely tools of biological functionality. This result sheds new light on the origin of cellular life, indicating that in evolutionary history, assignment of biological functions to cellular ingredients plays a crucial role. In this wider picture, even if (...)
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  47. Andrzej Mostowski (1955). Review: A. S. Esenin-Vol'pin, The Unprovability of Suslin's Hypothesis Without the Aid of the Axiom of Choice in the System of Axioms of Bernays-Mostowski. [REVIEW] Journal of Symbolic Logic 20 (2):181-182.score: 87.0
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  48. Patrick Hayes, Stevan Harnad, Donald R. Perlis & Ned Block (1992). Virtual Symposium on Virtual Mind. Minds and Machines 2 (3):217-238.score: 86.3
    When certain formal symbol systems (e.g., computer programs) are implemented as dynamic physical symbol systems (e.g., when they are run on a computer) their activity can be interpreted at higher levels (e.g., binary code can be interpreted as LISP, LISP code can be interpreted as English, and English can be interpreted as a meaningful conversation). These higher levels of interpretability are called "virtual" systems. If such a virtual system is interpretable as if it had a mind, (...)
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  49. Matteo Morganti (2009). Inherent Properties and Statistics with Individual Particles in Quantum Mechanics. Studies in History and Philosophy of Modern Physics 40 (3):223-231.score: 84.0
    This paper puts forward the hypothesis that the distinctive features of quantum statistics are exclusively determined by the nature of the properties it describes. In particular, all statistically relevant properties of identical quantum particles in many-particle systems are conjectured to be irreducible, ‘inherent’ properties only belonging to the whole system. This allows one to explain quantum statistics without endorsing the ‘Received View’ that particles are non-individuals, or postulating that quantum systems obey peculiar probability distributions, or assuming that there (...)
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  50. John L. Johnson (1996). Coordinate Transform Invariance. Foundations of Physics 26 (11):1529-1557.score: 84.0
    A four-dimensional operator is shown to contain the operator-generators for rotation, scale, reflections, and boosts. The hypothesis is advanced that a physical system changes under this operator by at most a complex phase factor due to invariance against the choice of menial frame. A canonical transform gives a simple relation between space-time and energy-momentum. The basic conserved quantity is a four-dimensional angular momentum and/or coupling constant. The differential of this function contains a second-order differential product which is (...)
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