Results for 'Symbol Grounding Problem'

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  1. The symbol grounding problem has been solved. so what's next.Luc Steels - 2008 - In Manuel de Vega, Arthur M. Glenberg & Arthur C. Graesser (eds.), Symbols and embodiment: debates on meaning and cognition. New York: Oxford University Press. pp. 223--244.
  2.  68
    The Difficulties in Symbol Grounding Problem and the Direction for Solving It.Jianhui Li & Haohao Mao - 2022 - Philosophies 7 (5):108.
    The symbol grounding problem (SGP) proposed by Stevan Harnad in 1990, originates from Searle’s “Chinese Room Argument” and refers to the problem of how a pure symbolic system acquires its meaning. While many solutions to this problem have been proposed, all of them have encountered inconsistencies to different extents. A recent approach for resolving the problem is to divide the SGP into hard and easy problems echoing the distinction between hard and easy problems for (...)
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  3. (1 other version)The symbol grounding problem.Stevan Harnad - 1990 - Physica D 42:335-346.
    There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis (...)
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  4. Which symbol grounding problem should we try to solve?Vincent C. Müller - 2015 - Journal of Experimental & Theoretical Artificial Intelligence 27 (1):73-78.
    Floridi and Taddeo propose a condition of “zero semantic commitment” for solutions to the grounding problem, and a solution to it. I argue briefly that their condition cannot be fulfilled, not even by their own solution. After a look at Luc Steels' very different competing suggestion, I suggest that we need to re-think what the problem is and what role the ‘goals’ in a system play in formulating the problem. On the basis of a proper understanding (...)
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  5. Meaning in Artificial Agents: The Symbol Grounding Problem Revisited.Dairon Rodríguez, Jorge Hermosillo & Bruno Lara - 2012 - Minds and Machines 22 (1):25-34.
    The Chinese room argument has presented a persistent headache in the search for Artificial Intelligence. Since it first appeared in the literature, various interpretations have been made, attempting to understand the problems posed by this thought experiment. Throughout all this time, some researchers in the Artificial Intelligence community have seen Symbol Grounding as proposed by Harnad as a solution to the Chinese room argument. The main thesis in this paper is that although related, these two issues present different (...)
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  6. Solving the symbol grounding problem: a critical review of fifteen years of research.Mariarosaria Taddeo & Luciano Floridi - unknown
    This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are (...)
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  7. Why there is no symbol grounding problem?Robert C. Cummins - 1996 - In Robert Cummins (ed.), Representations, Targets, and Attitudes. MIT Press.
     
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  8. A praxical solution of the symbol grounding problem.Mariarosaria Taddeo & Luciano Floridi - 2007 - Minds and Machines 17 (4):369-389.
    This article is the second step in our research into the Symbol Grounding Problem (SGP). In a previous work, we defined the main condition that must be satisfied by any strategy in order to provide a valid solution to the SGP, namely the zero semantic commitment condition (Z condition). We then showed that all the main strategies proposed so far fail to satisfy the Z condition, although they provide several important lessons to be followed by any new (...)
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  9.  49
    On Symbol Grounding.W. K. Yeap - 1993 - Idealistic Studies 23 (2-3):179-185.
    The symbol grounding problem is concerned with the question of how the knowledge used in AI programs, expressed as tokens in one form or another or simply symbols, could be grounded to the outside world. By grounding the symbols, it is meant that the system will know the actual objects, events, or states of affairs in the world to which each symbol refers and thus be worldly-wise. Solving this problem, it was hoped, would enable (...)
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  10.  49
    Semantics and symbol grounding in Turing machine processes.Anna Sarosiek - 2017 - Semina Scientiarum 16:211-223.
    The aim of the paper is to present the underlying reason of the unsolved symbol grounding problem. The Church-Turing Thesis states that a physical problem, for which there is an algorithm of solution, can be solved by a Turing machine, but machine operations neglect the semantic relationship between symbols and their meaning. Symbols are objects that are manipulated on rules based on their shapes. The computations are independent of the context, mental states, emotions, or feelings. The (...)
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  11.  48
    (1 other version)Social symbol grounding and language evolution.Paul Vogt & Federico Divina - 2007 - Interaction Studies 8 (1):31-52.
    This paper illustrates how external symbol grounding can be studied in simulations with large populations. We discuss how we can simulate language evolution in a relatively complex environment which has been developed in the context of the New Ties project. This project has the objective of evolving a cultural society and, in doing so, the agents have to evolve a communication system that is grounded in their interactions with their virtual environment and with other individuals. A preliminary experiment (...)
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  12. The hard and easy grounding problems (Comment on A. Cangelosi).Vincent C. Müller - 2011 - International Journal of Signs and Semiotic Systems 1 (1):70-70.
    I see four symbol grounding problems: 1) How can a purely computational mind acquire meaningful symbols? 2) How can we get a computational robot to show the right linguistic behavior? These two are misleading. I suggest an 'easy' and a 'hard' problem: 3) How can we explain and re-produce the behavioral ability and function of meaning in artificial computational agents?4) How does physics give rise to meaning?
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  13.  44
    Feature learning, multiresolution analysis, and symbol grounding.Karl F. MacDorman - 1998 - Behavioral and Brain Sciences 21 (1):32-33.
    Cognitive theories based on a fixed feature set suffer from frame and symbol grounding problems. Flexible features and other empirically acquired constraints (e.g., analog-to-analog mappings) provide a framework for letting extrinsic relations influence symbol manipulation. By offering a biologically plausible basis for feature learning, nonorthogonal multiresolution analysis and dimensionality reduction, informed by functional constraints, may contribute to a solution to the symbol grounding problem.
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  14.  49
    Grounding symbols in the analog world with neural nets a hybrid model.Stevan Harnad - unknown
    1.1 The predominant approach to cognitive modeling is still what has come to be called "computationalism" (Dietrich 1990, Harnad 1990b), the hypothesis that cognition is computation. The more recent rival approach is "connectionism" (Hanson & Burr 1990, McClelland & Rumelhart 1986), the hypothesis that cognition is a dynamic pattern of connections and activations in a "neural net." Are computationalism and connectionism really deeply different from one another, and if so, should they compete for cognitive hegemony, or should they collaborate? These (...)
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  15. Life after the symbol system metaphor.Karl F. MacDorman - 2007 - Interaction Studies 8 (1):143-158.
    After reviewing the papers in this special issue, I must conclude that brains are not syntactic engines, but control systems that orient to biological, interindividual, and cultural norms. By themselves, syntactic constraints both underdetermine and overdetermine cognitive operations. So, rather than serving as the basis for general cognition, they are just another kind of empirically acquired constraint. In humans, symbols emerge from a particular sensorimotor activity through a process of contextual broadening that depends on the coordination of conscious and nonconscious (...)
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  16.  71
    Symbolic Versus Associative Learning.John E. Hummel - 2010 - Cognitive Science 34 (6):958-965.
    Ramscar and colleagues (2010, this volume) describe the “feature-label-order” (FLO) effect on category learning and characterize it as a constraint on symbolic learning. I argue that FLO is neither a constraint on symbolic learning in the sense of “learning elements of a symbol system” (instead, it is an effect on nonsymbolic, association learning) nor is it, more than any other constraint on category learning, a constraint on symbolic learning in the sense of “solving the symbol grounding (...).”. (shrink)
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  17. Descartes Among the Robots: Computer Science and the Inner/outer Distinction.Graham White - 2011 - Minds and Machines 21 (2):179-202.
    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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  18. Computation is just interpretable symbol manipulation; cognition isn't.Stevan Harnad - 1994 - Minds and Machines 4 (4):379-90.
    Computation is interpretable symbol manipulation. Symbols are objects that are manipulated on the basis of rules operating only on theirshapes, which are arbitrary in relation to what they can be interpreted as meaning. Even if one accepts the Church/Turing Thesis that computation is unique, universal and very near omnipotent, not everything is a computer, because not everything can be given a systematic interpretation; and certainly everything can''t be givenevery systematic interpretation. But even after computers and computation have been successfully (...)
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  19. Bootstrapping Normativity.Graham White - 2011 - Philosophy and Technology 24 (1):35-53.
    We compare the role of Cartesian assumptions in the symbol grounding problem and in the Myth of the Given: We argue that the Sellars–McDowell critique of the Myth of the Given and, in particular, its use of the concept of normativity can provide useful resources for responding to the symbol grounding problem. We also describe the concepts of normativity at work in computer science and cognitive science: We argue that normative concepts are pervasive in (...)
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  20.  69
    Trade‐Offs Between Grounded and Abstract Representations: Evidence From Algebra Problem Solving.Kenneth R. Koedinger, Martha W. Alibali & Mitchell J. Nathan - 2008 - Cognitive Science 32 (2):366-397.
    This article explores the complementary strengths and weaknesses of grounded and abstract representations in the domain of early algebra. Abstract representations, such as algebraic symbols, are concise and easy to manipulate but are distanced from any physical referents. Grounded representations, such as verbal descriptions of situations, are more concrete and familiar, and they are more similar to physical objects and everyday experience. The complementary computational characteristics of grounded and abstract representations lead to trade‐offs in problem‐solving performance. In prior research (...)
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  21. Conceptual knowledge: Grounded in sensorimotor states, or a disembodied deus ex machina?Ezequiel Morsella, Carlos Montemayor, Jason Hubbard & Pareezad Zarolia - 2010 - Behavioral and Brain Sciences 33 (6):455-456.
    If embodied models no longer address the symbol grounding problem and a conceptual system can step in and resolve categorizations when embodied simulations fail, then perhaps the next step in theory-building is to isolate the unique contributions of embodied simulation. What is a disembodied conceptual system incapable of doing with respect to semantic processing or the categorization of smiles?
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  22.  22
    (1 other version)Non-Stupidity Condition and Pragmatics in Artificial Intelligence.Bojan Borstner & Niko Šetar - 2022 - Croatian Journal of Philosophy 22 (64):101-121.
    Symbol Grounding Problem is commonly considered one of the central challenges in the philosophy of artificial intelligence as its resolution is deemed necessary for bridging the gap between simple data processing and understanding of meaning and language. SGP has been addressed on numerous occasions with varying results, all resolution attempts having been severely, but for the most part justifiably, restricted by the Zero Semantic Commitment Condition. A further condition that demands explanatory power in terms of machine-to-human communication (...)
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  23. Equivalence of the Frame and Halting Problems.Eric Dietrich & Chris Fields - 2020 - Algorithms 13 (175):1-9.
    The open-domain Frame Problem is the problem of determining what features of an open task environment need to be updated following an action. Here we prove that the open-domain Frame Problem is equivalent to the Halting Problem and is therefore undecidable. We discuss two other open-domain problems closely related to the Frame Problem, the system identification problem and the symbol-grounding problem, and show that they are similarly undecidable. We then reformulate the (...)
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  24.  44
    Internal Perception: The Role of Bodily Information in Concepts and Word Mastery.Luigi Pastore & Sara Dellantonio - 2017 - Berlin, Heidelberg: Springer Berlin Heidelberg. Edited by Luigi Pastore.
    Chapter 1 First Person Access to Mental States. Mind Science and Subjective Qualities -/- Abstract. The philosophy of mind as we know it today starts with Ryle. What defines and at the same time differentiates it from the previous tradition of study on mind is the persuasion that any rigorous approach to mental phenomena must conform to the criteria of scientificity applied by the natural sciences, i.e. its investigations and results must be intersubjectively and publicly controllable. In Ryle’s view, philosophy (...)
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  25. Real Repugnance and Belief about Things-in-Themselves: A Problem and Kant's Three Solutions (including one about Symbols).Andrew Chignell - 2010 - In Benjamin J. Bruxvoort Lipscomb & James Krueger (eds.), Kant's Moral Metaphysics: God, Freedom, and Immortality. de Gruyter. pp. 177-209.
    Kant says that it can be rational to accept propositions on the basis of non-epistemic or broadly practical considerations, even if those propositions include “transcendental ideas” of supersensible objects. He also worries, however, about how such ideas (of freedom, the soul, noumenal grounds, God, the kingdom of ends, and things-in-themselves generally) acquire genuine positive content in the absence of an appropriate connection to intuitional experience. How can we be sure that the ideas are not empty “thought-entities (Gedankendinge)”—that is, speculative fancies (...)
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  26. No Qualia? No Meaning (and no AGI)!Marco Masi - manuscript
    The recent developments in artificial intelligence (AI), particularly in light of the impressive capabilities of transformer-based Large Language Models (LLMs), have reignited the discussion in cognitive science regarding whether computational devices could possess semantic understanding or whether they are merely mimicking human intelligence. Recent research has highlighted limitations in LLMs’ reasoning, suggesting that the gap between mere symbol manipulation (syntax) and deeper understanding (semantics) remains wide open. While LLMs overcome certain aspects of the symbol grounding problem (...)
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  27. The Meaning of Embodiment.Julian Kiverstein - 2012 - Topics in Cognitive Science 4 (4):740-758.
    There is substantial disagreement among philosophers of embodied cognitive science about the meaning of embodiment. In what follows, I describe three different views that can be found in the current literature. I show how this debate centers around the question of whether the science of embodied cognition can retain the computer theory of mind. One view, which I will label body functionalism, takes the body to play the functional role of linking external resources for problem solving with internal biological (...)
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  28.  12
    Analogical Symbols: The Role of Visual Cues in Long-Term Transfer.Zhe Chen, Lei Mo, Ryan Honomichl & Myeong-Ho Sohn - 2010 - Metaphor and Symbol 25 (2):93-113.
    We are reminded of relevant stories, tales, or symbols from long-term memory when facing a novel problem our daily lives. Visual cues are 1 tool known to facilitate reminding. In 2 experiments, Chinese students, who had experienced a folk tale many years ago during childhood, were asked to solve an analogous problem. We tested the hypothesis that a visual cue can help bridge the gap between a novel problem and a source analogy experienced in the distant past. (...)
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  29. Perceptual symbol systems.Lawrence W. Barsalou - 1999 - Behavioral and Brain Sciences 22 (4):577-660.
    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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  30.  23
    The Philosophy of Symbolic Forms, Volume 3: Phenomenology of Cognition.Ernst Cassirer & Steve G. Lofts - 2020 - Routledge.
    "In his Phenomenology of Cognition, Cassirer provides a comprehensive and systematic account of the dynamic process involved in the whole of human culture as it progresses from the world of myth and its feeling of social belonging to the highest abstractions of mathematics, logic and theoretical physics. Cassirer engages with the most sophisticated and cutting-edge work in fields ranging from ethnology to classics, egyptology and assyriology to ethology, brain science and psychology to logic, mathematics and theoretical physics. His command of (...)
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  31.  98
    Natural and Artificial Intelligence: A Comparative Analysis of Cognitive Aspects.Francesco Abbate - 2023 - Minds and Machines 33 (4):791-815.
    Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be (...)
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  32.  24
    The Symbolic Imagination: Plato and Contemporary Business Ethics.Paul T. Harper - 2019 - Journal of Business Ethics 168 (1):5-21.
    The business ethics field contains a number of explanations for the imagination’s influence on decision-making. This has benefited moral theorizing because approaches that utilize the imagination tend to acknowledge important biological and psychological forces that influence the way we understand situations, develop strategies for problem-solving, and choose courses of action. But, I argue, the broad range of approaches has also served as an obstacle to theory development in the field. Given the variety of theoretical and disciplinary approaches, coupled with (...)
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  33.  82
    People are infinitary symbol systems: No sensorimotor capacity necessary.Selmer Bringsjord - 2001
    Stevan Harnad and I seem to be thinking about many of the same issues. Sometimes we agree, sometimes we don't; but I always find his reasoning refreshing, his positions sensible, and the problems with which he's concerned to be of central importance to cognitive science. His "Grounding Symbols in the Analog World with Neural Nets" (= GS) is no exception. And GS not only exemplifies Harnad's virtues, it also provides a springboard for diving into Harnad- Bringsjord terrain.
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  34. On weak ground.Louis deRosset - 2014 - Review of Symbolic Logic 7 (4):713-744.
    Though the study of grounding is still in the early stages, Kit Fine, in ”The Pure Logic of Ground”, has made a seminal attempt at formalization. Formalization of this sort is supposed to bring clarity and precision to our theorizing, as it has to the study of other metaphysically important phenomena, like modality and vagueness. Unfortunately, as I will argue, Fine ties the formal treatment of grounding to the obscure notion of a weak ground. The obscurity of weak (...)
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  35. Other bodies, other minds: A machine incarnation of an old philosophical problem[REVIEW]Stevan Harnad - 1991 - Minds and Machines 1 (1):43-54.
    Explaining the mind by building machines with minds runs into the other-minds problem: How can we tell whether any body other than our own has a mind when the only way to know is by being the other body? In practice we all use some form of Turing Test: If it can do everything a body with a mind can do such that we can't tell them apart, we have no basis for doubting it has a mind. But what (...)
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  36.  21
    Linguistic Problems in the Investigation of Chinese Philosophy.Нanna Hnatovska & Vasyl Havronenko - 2023 - Bulletin of Taras Shevchenko National University of Kyiv Philosophy 2 (9):13-19.
    B a c k g r o u n d. The article is devoted to the analysis of the key directions of the study of the possible influence of the specifics of Chinese language culture on the content and nature of intellectual discourse, which is recognized as philosophical. Logic and ontology are the key areas of analysis of the possible influence of linguistic determinants on the intellectual discourse of China. Three main topics that attract the attention of researchers are the (...)
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  37. (1 other version)Minds, machines and Searle.Stevan Harnad - 1989 - Journal of Experimental and Theoretical Artificial Intelligence 1 (4):5-25.
    Searle's celebrated Chinese Room Argument has shaken the foundations of Artificial Intelligence. Many refutations have been attempted, but none seem convincing. This paper is an attempt to sort out explicitly the assumptions and the logical, methodological and empirical points of disagreement. Searle is shown to have underestimated some features of computer modeling, but the heart of the issue turns out to be an empirical question about the scope and limits of the purely symbolic model of the mind. Nonsymbolic modeling turns (...)
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  38.  57
    Foundations of AI: The big issues.David Kirsh - 1991 - Artificial Intelligence 47 (1-3):3-30.
    The objective of research in the foundations of Al is to explore such basic questions as: What is a theory in Al? What are the most abstract assumptions underlying the competing visions of intelligence? What are the basic arguments for and against each assumption? In this essay I discuss five foundational issues: (1) Core Al is the study of conceptualization and should begin with knowledge level theories. (2) Cognition can be studied as a disembodied process without solving the symbol (...)
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  39.  35
    A rhythm recognition computer program to advocate interactivist perception.Jean-Christophe Buisson - 2004 - Cognitive Science 28 (1):75-88.
    This paper advocates the main ideas of the interactive model of representation of Mark Bickhard and the assimilation/accommodation framework of Jean Piaget, through a rhythm recognition demonstration program. Although completely unsupervised, the program progressively learns to recognize more and more complex rhythms struck on the user's keyboard. It does so without any recording of the input flow, and without any pattern matching in the usual sense. On the contrary, internal processes are dynamically constructed to follow and anticipate the user's actions. (...)
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  40.  11
    Scriptural Grounds for Concrete Moral Norms.Benedict M. Ashley - 1988 - The Thomist 52 (1):1-22.
    In lieu of an abstract, here is a brief excerpt of the content:SCRIPTURAL GROUNDS FOR CONCRETE MORAL NORMS 1. Is JJ1oral Theology Really Theology? 0 BE CHRISTIAN theology moral theology ought to be firmly grounded in the Bible as understood in the living tradition of the Church. Yet the moralist who asks help from the biblicist today is to be met with a host cf objections.1 I will mention eight I have encountered: l) Attempts to develop a biblical theology unified (...)
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  41. Contextual Emergence of Mental States From Neurodynamics.Harald Atmanspacher - unknown
    The emergence of mental states from neural states by partitioning the neural phase space is analyzed in terms of symbolic dynamics. Well-defined mental states provide contexts inducing a criterion of structural stability for the neurodynamics that can be implemented by particular partitions. This leads to distinguished subshifts of finite type that are either cyclic or irreducible. Cyclic shifts correspond to asymptotically stable fixed points or limit tori whereas irreducible shifts are obtained from generating partitions of mixing hyperbolic systems. These stability (...)
     
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  42.  87
    Typ-Ken (an Amalgam of Type and Token) Drives Infosphere.Yukio-Pegio Gunji, Takayuki Niizato, Hisashi Murakami & Iori Tani - 2010 - Knowledge, Technology & Policy 23 (1):227-251.
    Floridi’s infosphere consisting of informational reality is estimated and delineated by introducing the new notion of Typ-Ken, an undifferentiated amalgam of type and token that can be expressed as either type or token dependent on contingent ontological commitment. First, we elaborate Floridi’s system, level of abstraction (LoA), model, and structure scheme, which is proposed to reconcile ontic with epistemic structural reality, and obtain the duality of type and token inherited in the relationship between LoA and model. While we focus on (...)
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  43.  25
    Codes, communication and cognition.Stevan Harnad - 2019 - Behavioral and Brain Sciences 42.
    Brette criticizes the notion of neural coding because it seems to entail that neural signals need to “decoded” by or for some receiver in the head. If that were so, then neural coding would indeed be homuncular, requiring an entity to decipher the code. But I think Brette's plea to think instead in terms of complex, interactive causal throughput is preaching to the converted. Turing has already shown the way. In any case, the metaphor of neural coding has little to (...)
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  44. The ground-negative fragment of first-order logic is πp2-complete.Andrei Voronkov - 1999 - Journal of Symbolic Logic 64 (3):984 - 990.
    We prove that for a natural class of first-order formulas the validity problem is Π p 2 -complete.
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  45. Beyond the computer metaphor: Behaviour as interaction.Paul Cisek - 1999 - Journal of Consciousness Studies 6 (11-12):11-12.
    Behaviour is often described as the computation of a response to a stimulus. This description is incomplete in an important way because it only examines what occurs between the reception of stimulus information and the generation of an action. Behaviour is more correctly described as a control process where actions are performed in order to affect perceptions. This closed-loop nature of behaviour is de-emphasized in modern discussions of brain function, leading to a number of artificial mysteries. A notable example is (...)
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  46.  44
    Theory of philosophy as a science of the symbolic.Angele Kremer-Marietti - 1990 - Argumentation 4 (3):363-373.
    This study tries to put the foundations of a theory of reasoning on the ground of philosophy as philosophy: what are the presupposed terms of the philosophical research, and what they are meaning. It intends to separate words from their “evident” meaning and to receive them as “symbolic items”. Symbolization is the most important way of proceeding in philosophy. Philosophers are usually not aware of this symbolical process. Thus, the structure of “knowing” in philosophy is presented as a way of (...)
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  47.  79
    The State Space of Artificial Intelligence.Holger Lyre - 2020 - Minds and Machines 30 (3):325-347.
    The goal of the paper is to develop and propose a general model of the state space of AI. Given the breathtaking progress in AI research and technologies in recent years, such conceptual work is of substantial theoretical interest. The present AI hype is mainly driven by the triumph of deep learning neural networks. As the distinguishing feature of such networks is the ability to self-learn, self-learning is identified as one important dimension of the AI state space. Another dimension is (...)
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  48.  50
    Modernity as a rhetorical problem: Phronēsis , forms, and forums in norms of rhetorical culture.James Arnt Aune - 2008 - Philosophy and Rhetoric 41 (4):pp. 402-420.
    In lieu of an abstract, here is a brief excerpt of the content:Modernity as a Rhetorical Problem: Phronēsis, Forms, and Forums in Norms of Rhetorical CultureJames Arnt AuneThe true paradises are the paradises that we’ve lost.—Marcel Proust, The Past RegainedThomas B. Farrell’s Norms of Rhetorical Culture (1993, 6) remains both a masterly synthesis of previous constructive work in rhetorical theory and the essential starting point for anyone committed to reconciling the practical impulses of Aristotelian rhetoric, ethics, and politics with (...)
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  49. The foundational problem of logic.Gila Sher - 2013 - Bulletin of Symbolic Logic 19 (2):145-198.
    The construction of a systematic philosophical foundation for logic is a notoriously difficult problem. In Part One I suggest that the problem is in large part methodological, having to do with the common philosophical conception of “providing a foundation”. I offer an alternative to the common methodology which combines a strong foundational requirement with the use of non-traditional, holistic tools to achieve this result. In Part Two I delineate an outline of a foundation for logic, employing the new (...)
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  50.  28
    The ttt is not the final word.Stevan Harnad - unknown
    My purpose is to explain, first, that there is an alternative to Harnad's version of the symbol grounding problem, which is known as the problem of primitives; second, that there is an alternative to his solution (which is externalist) in the form of a dispositional conception (which is internalist); and, third, that, while the TTT, properly understood, may provide partial and fallible evidence for the presence of similar mental powers, it cannot supply conclusive proof, because more (...)
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