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  1. Robert F. Hadley (2008). Consistency, Turing Computability and Gödel's First Incompleteness Theorem. Minds and Machines 18 (1):1-15.
    It is well understood and appreciated that Gödel’s Incompleteness Theorems apply to sufficiently strong, formal deductive systems. In particular, the theorems apply to systems which are adequate for conventional number theory. Less well known is that there exist algorithms which can be applied to such a system to generate a gödel-sentence for that system. Although the generation of a sentence is not equivalent to proving its truth, the present paper argues that the existence of these algorithms, when conjoined with Gödel’s (...)
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  2. Robert F. Hadley (2006). Neural Circuits, Matrices, and Conjunctive Binding. Behavioral and Brain Sciences 29 (1):80-80.
    It is argued that van der Velde and de Kamps employ binding circuitry that effectively constitutes a form of conjunctive binding. Analogies with prior systems are discussed and hypothetical origins of binding circuitry are examined for credibility.
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  3. Marius Vilcu & Robert F. Hadley (2005). Two Apparent 'Counterexamples' to Marcus: A Closer Look. [REVIEW] Minds and Machines 15 (3-4):359-382.
    Marcus et al.’s experiment (1999) concerning infant ability to distinguish between differing syntactic structures has prompted connectionists to strive to show that certain types of neural networks can mimic the infants’ results. In this paper we take a closer look at two such attempts: Shultz and Bale [Shultz, T.R. and Bale, A.C. (2001), Infancy 2, pp. 501–536] Altmann and Dienes [Altmann, G.T.M. and Dienes, Z. (1999) Science 248, p. 875a]. We were not only interested in how well these two models (...)
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  4. Robert F. Hadley (2004). On the Proper Treatment of Semantic Systematicity. Minds and Machines 14 (2):145-172.
    The past decade has witnessed the emergence of a novel stance on semantic representation, and its relationship to context sensitivity. Connectionist-minded philosophers, including Clark and van Gelder, have espoused the merits of viewing hidden-layer, context-sensitive representations as possessing semantic content, where this content is partially revealed via the representations'' position in vector space. In recent work, Bodén and Niklasson have incorporated a variant of this view of semantics within their conception of semantic systematicity. Moreover, Bodén and Niklasson contend that they (...)
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  5. Robert F. Hadley (1999). Connectionism and Novel Combinations of Skills: Implications for Cognitive Architecture. [REVIEW] Minds and Machines 9 (2):197-221.
    In the late 1980s, there were many who heralded the emergence of connectionism as a new paradigm – one which would eventually displace the classically symbolic methods then dominant in AI and Cognitive Science. At present, there remain influential connectionists who continue to defend connectionism as a more realistic paradigm for modeling cognition, at all levels of abstraction, than the classical methods of AI. Not infrequently, one encounters arguments along these lines: given what we know about neurophysiology, it is just (...)
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  6. Robert F. Hadley (1997). Cognition, Systematicity, and Nomic Necessity. Mind and Language 12 (2):137-53.
  7. Robert F. Hadley (1997). Explaining Systematicity: A Reply to Kenneth Aizawa. [REVIEW] Minds and Machines 12 (4):571-79.
    In his discussion of results which I (with Michael Hayward) recently reported in this journal, Kenneth Aizawa takes issue with two of our conclusions, which are: (a) that our connectionist model provides a basis for explaining systematicity within the realm of sentence comprehension, and subject to a limited range of syntax (b) that the model does not employ structure-sensitive processing, and that this is clearly true in the early stages of the network''s training. Ultimately, Aizawa rejects both (a) and (b) (...)
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  8. Robert F. Hadley & M. B. Hayward (1997). Strong Semantic Systematicity From Hebbian Connectionist Learning. Minds and Machines 7 (1):1-55.
    Fodor's and Pylyshyn's stand on systematicity in thought and language has been debated and criticized. Van Gelder and Niklasson, among others, have argued that Fodor and Pylyshyn offer no precise definition of systematicity. However, our concern here is with a learning based formulation of that concept. In particular, Hadley has proposed that a network exhibits strong semantic systematicity when, as a result of training, it can assign appropriate meaning representations to novel sentences (both simple and embedded) which contain words in (...)
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  9. Robert F. Hadley (1995). The 'Explicit-Implicit' Distinction. Minds and Machines 5 (2):219-42.
    Much of traditional AI exemplifies the explicit representation paradigm, and during the late 1980''s a heated debate arose between the classical and connectionist camps as to whether beliefs and rules receive an explicit or implicit representation in human cognition. In a recent paper, Kirsh (1990) questions the coherence of the fundamental distinction underlying this debate. He argues that our basic intuitions concerning explicit and implicit representations are not only confused but inconsistent. Ultimately, Kirsh proposes a new formulation of the distinction, (...)
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  10. Robert F. Hadley (1994). Systematicity in Connectionist Language Learning. Mind and Language 9 (3):247-72.
  11. Robert F. Hadley (1994). Systematicity Revisited. Mind and Language 9 (4):431-44.
  12. Robert F. Hadley (1993). Connectionism, Explicit Rules, and Symbolic Manipulation. Minds and Machines 3 (2):183-200.
    At present, the prevailing Connectionist methodology forrepresenting rules is toimplicitly embody rules in neurally-wired networks. That is, the methodology adopts the stance that rules must either be hard-wired or trained into neural structures, rather than represented via explicit symbolic structures. Even recent attempts to implementproduction systems within connectionist networks have assumed that condition-action rules (or rule schema) are to be embodied in thestructure of individual networks. Such networks must be grown or trained over a significant span of time. However, arguments (...)
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  13. Robert F. Hadley (1991). A Sense-Based, Process Model of Belief. Minds and Machines 1 (3):279-320.
    A process-oriented model of belief is presented which permits the representation of nested propositional attitudes within first-order logic. The model (NIM, for nested intensional model) is axiomatized, sense-based (via intensions), and sanctions inferences involving nested epistemic attitudes, with different agents and different times. Because NIM is grounded upon senses, it provides a framework in which agents may reason about the beliefs of another agent while remaining neutral with respect to the syntactic forms used to express the latter agent's beliefs. Moreover, (...)
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  14. Robert F. Hadley (1991). The Many Uses of 'Belief' in AI. Minds and Machines 1 (1):55-74.
    Within AI and the cognitively related disciplines, there exist a multiplicity of uses of belief. On the face of it, these differing uses reflect differing views about the nature of an objective phenomenon called belief. In this paper I distinguish six distinct ways in which belief is used in AI. I shall argue that not all these uses reflect a difference of opinion about an objective feature of reality. Rather, in some cases, the differing uses reflect differing concerns with special (...)
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  15. Robert F. Hadley (1990). Connectionism, Rule-Following, and Symbolic Manipulation. Proc AAAI 3 (2):183-200.
  16. Robert F. Hadley (1990). Truth Conditions and Procedural Semantics. In Philip P. Hanson (ed.), Information, Language and Cognition. University of British Columbia Press.
  17. Robert F. Hadley (1989). A Default‐Oriented Theory of Procedural Semantics. Cognitive Science 13 (1):107-137.
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  18. Robert F. Hadley (1987). Godel, Lucas, and Mechanical Models of Mind. Computational Intelligence 3:57-63.
  19. Robert F. Hadley (1978). Possibility, Necessity, and Logical Truth. Analysis 38 (4):182 - 186.
    An earlier article by the author, "quine and strawson on logical theory" ("analysis" volume 34, pages 207-208), is expanded and defended against criticisms made by charles sayward in "the province of logic" ("analysis" volume 36, pages 47-48). it is shown that quine's definition of logical truth presupposes an understanding of "possibility," even if the term 'sentence' is used set-theoretically, and that if quine is allowed the concept of "possibility," then strawson must be allowed modal concepts for his purposes. the traditional (...)
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  20. Robert F. Hadley (1974). Quine and Strawson on Logical Theory. Analysis 34 (6):207 - 208.
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