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  1. James H. Fetzer (1991). Philosophy and Cognitive Science. Paragon House.
  2.  99
    James H. Fetzer (1990). Artificial Intelligence: Its Scope and Limits. Kluwer.
    1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..
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  3. James H. Fetzer (1993). Philosophy of Science. Paragon House Publishers.
  4. James H. Fetzer, George N. Schlesinger & David Shatz (1991). Definitions and Definability Philosophical Perspectives.
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  5. James H. Fetzer (1989). Language and Mentality: Computational, Representational, and Dispositional Conceptions. Behaviorism 17 (1):21-39.
    The purpose of this paper is to explore three alternative frameworks for understanding the nature of language and mentality, which accent syntactical, semantical, and pragmatical aspects of the phenomena with which they are concerned, respectively. Although the computational conception currently exerts considerable appeal, its defensibility appears to hinge upon an extremely implausible theory of the relation of form to content. Similarly, while the representational approach has much to recommend it, its range is essentially restricted to those units of language that (...)
     
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  6.  61
    James H. Fetzer (2004). Information: Does It Have to Be True? [REVIEW] Minds and Machines 14 (2):223-229.
    Luciano Floridi (2003) offers a theory of information as a strongly semantic notion, according to which information encapsulates truth, thereby making truth a necessary condition for a sentence to qualify as information. While Floridi provides an impressive development of this position, the aspects of his approach of greatest philosophical significance are its foundations rather than its formalization. He rejects the conception of information as meaningful data, which entails at least three theses – that information can be false; that tautologies are (...)
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  7.  11
    James H. Fetzer (1992). Connectionism and Cognition: Why Fodor and Pylyshyn Are Wrong. In A. Clark & Ronald Lutz (eds.), Connectionism in Context. Springer-Verlag 305-319.
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  8.  82
    James H. Fetzer (1988). Program Verification: The Very Idea. Communications of the Acm 31 (9):1048--1063.
    The notion of program verification appears to trade upon an equivocation. Algorithms, as logical structures, are appropriate subjects for deductive verification. Programs, as causal models of those structures, are not. The success of program verification as a generally applicable and completely reliable method for guaranteeing program performance is not even a theoretical possibility.
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  9. James H. Fetzer (1974). The Likeness of Lawlikeness. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1974:377 - 391.
    The thesis of this paper is that extensional language alone provides an essentially inadequate foundation for the logical formalization of any lawlike statement. The arguments presented are intended to demonstrate that lawlike sentences are logically general dispositional statements requiring an essentially intensional reduction sentence formulation. By introducing a non-extensional logical operator, the 'fork', the difference between universal and statistical laws emerges in a distinction between dispositional predicates of universal strength as opposed to those of merely statistical strength. While the logical (...)
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  10.  93
    James H. Fetzer (1991). Are There Laws of Nature? Philosophical Books 32 (2):65-75.
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  11.  9
    James H. Fetzer (1984). Scientific Knowledge, Causation, Explanation, and Corroboration. Tijdschrift Voor Filosofie 46 (3):541-542.
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  12. James H. Fetzer (1991). Frederick Suppe, The Semantic Conception of Theories and Scientific Realism Reviewed By. Philosophy in Review 11 (5):364-367.
     
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  13.  18
    James H. Fetzer & Donald E. Nute (1979). Syntax, Semantics, and Ontology: A Probabilistic Causal Calculus. Synthese 40 (3):453 - 495.
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  14.  3
    James H. Fetzer (2013). Evolving Consciousness: The Very Idea! In Liz Swan (ed.), Origins of Mind. 225--242.
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  15. J. Fetzer (ed.) (1988). Probability and Causality. D. Reidel.
  16.  46
    James H. Fetzer (2004). Disinformation: The Use of False Information. [REVIEW] Minds and Machines 14 (2):231-240.
    The distinction between misinformation and disinformation becomes especially important in political, editorial, and advertising contexts, where sources may make deliberate efforts to mislead, deceive, or confuse an audience in order to promote their personal, religious, or ideological objectives. The difference consists in having an agenda. It thus bears comparison with lying, because lies are assertions that are false, that are known to be false, and that are asserted with the intention to mislead, deceive, or confuse. One context in which disinformation (...)
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  17.  11
    James H. Fetzer (1977). A World of Dispositions. Synthese 34 (4):397 - 421.
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  18.  14
    James H. Fetzer (1977). Reichenbach, Reference Classes, and Single Case 'Probabilities'. Synthese 34 (2):185 - 217.
  19.  21
    James H. Fetzer (1999). The Role Of Models In Computer Science. The Monist 82 (1):20-36.
    Taking Brian Cantwell Smith’s study, “Limits of Correctness in Computers,” as its point of departure, this article explores the role of models in computer science. Smith identifies two kinds of models that play an important role, where specifications are models of problems and programs are models of possible solutions. Both presuppose the existence of conceptualizations as ways of conceiving the world “in certain delimited ways.” But high-level programming languages also function as models of virtual (or abstract) machines, while low-level programming (...)
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  20.  20
    James H. Fetzer (1985). How the Laws of Physics Lie. [REVIEW] Philosophical Books 26 (2):120-124.
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  21. J. H. Fetzer (2004). Information, Misinformation, and Disinformation. Minds and Machines 14 (2):223-229.
     
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  22.  16
    James H. Fetzer (1974). A Single Case Propensity Theory of Explanation. Synthese 28 (2):171 - 198.
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  23.  51
    James H. Fetzer (2002). Propensities and Frequencies: Inference to the Best Explanation. Synthese 132 (1-2):27 - 61.
    An approach to inference to the best explanation integrating a Popperianconception of natural laws together with a modified Hempelian account of explanation, one the one hand, and Hacking's law of likelihood (in its nomicguise), on the other, which provides a robust abductivist model of sciencethat appears to overcome the obstacles that confront its inductivist,deductivist, and hypothetico-deductivist alternatives.This philosophy of scienceclarifies and illuminates some fundamental aspects of ontology and epistemology, especially concerning the relations between frequencies and propensities. Among the most important (...)
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  24. James H. Fetzer (1990). The Frame Problem: Artificial Intelligence Meets David Hume. International Journal of Expert Systems 3:219-232.
  25.  61
    James H. Fetzer (1997). Thinking and Computing: Computers as Special Kinds of Signs. [REVIEW] Minds and Machines 7 (3):345-364.
    Cognitive science has been dominated by the computational conception that cognition is computation across representations. To the extent to which cognition as computation across representations is supposed to be a purposive, meaningful, algorithmic, problem-solving activity, however, computers appear to be incapable of cognition. They are devices that can facilitate computations on the basis of semantic grounding relations as special kinds of signs. Even their algorithmic, problem-solving character arises from their interpretation by human users. Strictly speaking, computers as such — apart (...)
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  26.  19
    James H. Fetzer & Donald E. Nute (1980). A Probabilistic Causal Calculus: Conflicting Conceptions. Synthese 44 (2):241 - 246.
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  27.  38
    James H. Fetzer (ed.) (2000). Science, Explanation, and Rationality: Aspects of the Philosophy of Carl G. Hempel. Oxford University Press.
    Carl G. Hempel exerted greater influence upon philosophers of science than any other figure during the 20th century. In this far-reaching collection, distinguished philosophers contribute valuable studies that illuminate and clarify the central problems to which Hempel was devoted. The essays enhance our understanding of the development of logical empiricism as the major intellectual influence for scientifically-oriented philosophers and philosophically-minded scientists of the 20th century.
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  28.  15
    James H. Fetzer & Donald E. Nute (1981). A Probabilistic Causal Calculus: Conflicting Conceptions. Synthese 48 (3):241 - 246.
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  29.  7
    James H. Fetzer (1975). On the Historical Explanation of Unique Events. Theory and Decision 6 (1):87-97.
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  30. J. H. Fetzer & P. Humphreys (eds.) (1998). The New Theory of Reference: Kripke, Marcus, and its Origins. Kluwer.
  31.  16
    Paul Sheldon Davies, James H. Fetzer & Thomas R. Foster (1995). Logical Reasoning and Domain Specificity. Biology and Philosophy 10 (1):1-37.
    The social exchange theory of reasoning, which is championed by Leda Cosmides and John Tooby, falls under the general rubric evolutionary psychology and asserts that human reasoning is governed by content-dependent, domain-specific, evolutionarily-derived algorithms. According to Cosmides and Tooby, the presumptive existence of what they call cheater-detection algorithms disconfirms the claim that we reason via general-purpose mechanisms or via inductively acquired principles. We contend that the Cosmides/Tooby arguments in favor of domain-specific algorithms or evolutionarily-derived mechanisms fail and that the notion (...)
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  32.  8
    James H. Fetzer (1994). Mental Algorithms: Are Minds Computational Systems? Pragmatics and Cognition 21 (1):1-29.
    The idea that human thought requires the execution of mental algorithms provides a foundation for research programs in cognitive science, which are largely based upon the computational conception of language and mentality. Consideration is given to recent work by Penrose, Searle, and Cleland, who supply various grounds for disputing computationalism. These grounds in turn qualify as reasons for preferring a non-computational, semiotic approach, which can account for them as predictable manifestations of a more adquate conception. Thinking does not ordinarily require (...)
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  33.  8
    James H. Fetzer (1982). Probabilistic Explanations. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:194-207.
    The purpose of this paper is to provide a systematic defense of the single-case propensity account of probabilistic explanation from the criticisms advanced by Hanna and by Humphreys and to offer a critical appraisal of the aleatory conception advanced by Humphreys and of the deductive-nomological-probabilistic approach Railton has proposed. The principal conclusion supported by this analysis is that the Requirements of Maximal Specificity and of Strict Maximal Specificity afford the foundation for completely objective explanations of probabilistic explananda, so long as (...)
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  34.  9
    James H. Fetzer (2002). In Memoriam: Wesley C. Salmon (1925-2001). Synthese 132 (1-2):1 - 3.
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  35.  55
    James H. Fetzer (1991). Philosophical Aspects of Program Verification. Minds and Machines 1 (2):197-216.
    A debate over the theoretical capabilities of formal methods in computer science has raged for more than two years now. The function of this paper is to summarize the key elements of this debate and to respond to important criticisms others have advanced by placing these issues within a broader context of philosophical considerations about the nature of hardware and of software and about the kinds of knowledge that we have the capacity to acquire concerning their performance.
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  36.  71
    James H. Fetzer (2011). Evolution and Atheism: Has Griffin Reconciled Science and Religion? Synthese 178 (2):381 - 396.
    The distinguished theologian, David Ray Griffin, has advanced a set of thirteen theses intended to characterize (what he calls) "Neo-Darwinism" and which he contrasts with "Intelligent Design". Griffin maintains that Neo-Darwinism is "atheistic" in forgoing a creator but suggests that, by adopting a more modest scientific naturalism and embracing a more naturalistic theology, it is possible to find "a third way" that reconciles religion and science. The considerations adduced here suggest that Griffin has promised more than he can deliver. On (...)
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  37.  24
    James H. Fetzer (1983). Probability and Objectivity in Deterministic and Indeterministic Situations. Synthese 57 (3):367--86.
    This paper pursues the question, To what extent does the propensity approach to probability contribute to plausible solutions to various anomalies which occur in quantum mechanics? The position I shall defend is that of the three interpretations — the frequency, the subjective, and the propensity — only the third accommodates the possibility, in principle, of providing a realistic interpretation of ontic indeterminism. If these considerations are correct, then they lend support to Popper's contention that the propensity construction tends to remove (...)
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  38.  15
    James H. Fetzer (1997). Escaping the Propositional Prison. The Monist 80 (3):368-388.
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  39. James H. Fetzer & Wesley C. Salmon (1988). Probability and Causality Essays in Honor of Wesley C. Salmon. Monograph Collection (Matt - Pseudo).
     
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  40.  5
    James H. Fetzer (1994). Creative Thinking Presupposes the Capacity for Thought. Behavioral and Brain Sciences 17 (3):539-540.
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  41.  17
    James H. Fetzer (1986). Methodological Individualism: Singular Causal Systems and Their Population Manifestations. Synthese 68 (1):99 - 128.
    The purpose of this essay is to investigate the properties of singular causal systems and their population manifestations, with special concern for the thesis of methodological individualism, which claims that there are no properties of social groups that cannot be adequately explained exclusively by reference to properties of individual members of those groups, i.e., at the level of individuals. Individuals, however, may be viewed as singular causal systems, i.e., as instantiations of (arrangements of) dispositional properties. From this perspective, methodological individualism (...)
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  42.  21
    James H. Fetzer (1981). Probability and Explanation. Synthese 48 (3):371 - 408.
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  43.  16
    James H. Fetzer (1978). On Mellor on Dispositions. Philosophia 7 (3-4):651-660.
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  44. Paul Humphreys & James Fetzer (eds.) (1998). The New Theory of Reference. Kluwer.
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  45.  24
    James H. Fetzer (1990). Evolution, Rationality and Testability. Synthese 82 (3):423-39.
    Cosmides, Wason, and Johnson-Laird, among others, have suggested evidence that reasoning abilities tend to be domain specific, insofar as humans do not appear to acquire capacities for logical reasoning that are applicable across different contexts. Unfortunately, the significance of these findings depends upon the specific variety of logical reasoning under consideration. Indeed, there seem to be at least three grounds for doubting such conclusions, since: (1) tests of reasoning involving the use of material conditionals may not be appropriate for representing (...)
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  46. P. S. Davies, J. Fetzer & T. Foster (1995). Domain Specificity a Social Exchange Reasoning: A Critique of the Social Exchange Theory of Reasoning. Biology and Philosophy 10:1-37.
     
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  47.  19
    James H. Fetzer (1974). On “Epistemic Possibility”. Philosophia 4 (2-3):327-335.
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  48.  40
    James H. Fetzer (2003). Consciousness and Cognition: Semiotic Conceptions of Bodies and Minds. In Quentin Smith & Aleksandar Jokic (eds.), Consciousness: New Philosophical Perspectives. Oxford University Press 295.
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  49. James H. Fetzer (1993). Glossary of Epistemology/Philosophy of Science. Paragon House.
     
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  50. James H. Fetzer (1989). Michael Tooley, Causation: A Realist Approach Reviewed By. Philosophy in Review 9 (3):121-124.
     
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