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  1. Ronald L. Chrisley, Contents.
    2.4 The Example: Infants and object-(im)permanence : : : : : : : : : : : : : : 17 2.4.1 Why a contentful account is warranted: Perspectival sensitivity : : : 17 2.4.2 The \searching under a cloth" and \AB" data : : : : : : : : : : : : 24 2.4.3 Two constraints on objectuality : : : : : : : : : : : : : Error: Illegal entry in bfrange block in (...)
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  2. Ronald L. Chrisley, Connectionism, Cognitive Maps & the Development of Objectivity.
    It is claimed that there are pre-objective phenomena, which cognitive science should explain by employing the notion of non-conceptual representational content. It is argued that a match between parallel distributed processing (PDP) and non-conceptual content (NCC) not only provides a means of refuting recent criticisms of PDP as a cognitive architecture; it also provides a vehicle for NCC that is required by naturalism. A connectionist cognitive mapping algorithm is used as a case study to examine the affinities between PDP and (...)
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  3. Ronald L. Chrisley, Externalism Before Language: The Real Reason Why “Thoughts Ain't in the Head”.
    It is argued that standard arguments for the Externalism of mental states do not succeed in the case of pre-linguistic mental states. Further, it is noted that standard arguments for Internalism appeal to the principle that our individuation of mental states should be driven by what states are explanatory in our best cognitive science. This principle is used against the Internalist to reject the necessity of narrow individuation of mental states, even in the prelinguistic case. This is done by showing (...)
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  4. Ronald L. Chrisley, Learning in Non-Superpositional Quantum Neurocomputers.
    In both the search for ever smaller and faster computational devices, and the search for a computational understanding of biological systems such as the brain, one is naturally led to consider the possibility of computational devices the size of cells, molecules, atoms, or on even smaller scales. Indeed, it has been pointed out Braunstein, 1995] that if trends over the last forty years continue, we may reach atomic-scale computation by the year 2010 Keyes, 1988]. This move down in scale takes (...)
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  5. Ronald L. Chrisley, Non-Compositional Representation in Connectionist Networks.
    have context-sensitive constituents, but rather because they sometimes have no constituents at all. The argument to be rejected depends on the assumption that one can only assign propositional contents to representations if one starts by assigning sub-propositional contents to atomic representations. I give some philosophical arguments and present a counterexample to show that this assumption is mistaken.
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  6. Ronald L. Chrisley, (Ronc@Cogs.Susx.Ac. Uk).
    imply that computational states are not "real", and cannot, for example, provide a foundation for the cognitive sciences. In particular, Putnam has argued that every ordinary open physical system realizes every abstract finite automaton, implying that the fact that a particular computational characterization applies to a physical system does not tell one anything about the nature of that system. Putnam's argument is scrutinized, and found inadequate because, among other things, it employs a notion of causation that is too weak. I (...)
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  7. Ronald L. Chrisley, Singular Terms and Reference: Evans and "Julius&Quot.
    used) (Evans 1982: 31). He dubbed these terms "descriptive names"1, and used them as a foil against which to test several theories of reference: Frege's, Russell's, and his own.
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  8. Ronald L. Chrisley, Transparent Computationalism.
    Summary. A distinction is made between two senses of the claim “cognition is computation”. One sense, the opaque reading, takes computation to be whatever is described by our current computational theory and claims that cognition is best understood in terms of that theory. The transparent reading, which has its primary allegiance to the phenomenon of computation, rather than to any particular theory of it, is the claim that the best account of cognition will be given by whatever theory turns out (...)
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  9. Ronald L. Chrisley, Weak Strong AI: An Elaboration of the English Reply to the Chinese Room.
    Searle (1980) constructed the Chinese Room (CR) to argue against what he called \Strong AI": the claim that a computer can understand by virtue of running a program of the right sort. Margaret Boden (1990), in giving the English Reply to the Chinese Room argument, has pointed out that there isunderstanding in the Chinese Room: the understanding required to recognize the symbols, the understanding of English required to read the rulebook, etc. I elaborate on and defend this response to Searle. (...)
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  10. Aaron Sloman & Ronald L. Chrisley (2003). Virtual Machines and Consciousness. Journal of Consciousness Studies 10 (4-5):133-172.
    Replication or even modelling of consciousness in machines requires some clarifications and refinements of our concept of consciousness. Design of, construction of, and interaction with artificial systems can itself assist in this conceptual development. We start with the tentative hypothesis that although the word “consciousness” has no well-defined meaning, it is used to refer to aspects of human and animal informationprocessing. We then argue that we can enhance our understanding of what these aspects might be by designing and building virtual-machine (...)
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  11. Ronald L. Chrisley (2001). A View From Anywhere: Prospects for an Objective Understanding of Consciousness. In Paavo Pylkkanen & Tere Vaden (eds.), Dimensions of Conscious Experience. John Benjamins.
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  12. Ronald L. Chrisley (2001). A View From Anywhere Prospects for an Objective Understanding. In Paavo Pylkkanen & Tere Vaden (eds.), Dimensions of Conscious Experience. John Benjamins. 37--3.
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  13. Ronald L. Chrisley (1998). What Might Dynamical Intentionality Be, If Not Computation? Behavioral and Brain Sciences 21 (5):634-635.
    (1) Van Gelder's concession that the dynamical hypothesis is not in opposition to computation in general does not agree well with his anticomputational stance. (2) There are problems with the claim that dynamic systems allow for nonrepresentational aspects of computation in a way in which digital computation cannot. (3) There are two senses of the “cognition is computation” claim and van Gelder argues against only one of them. (4) Dynamical systems as characterized in the target article share problems of universal (...)
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  14. Ronald L. Chrisley (1994). European Review of Philosophy, Volume 1: Philosophy of Mind. Stanford: CSLI Publications.
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  15. Ronald L. Chrisley (1994). Taking Embodiment Seriously: Nonconceptual Content and Robotics. In Kenneth M. Ford, C. Glymour & Patrick Hayes (eds.), Android Epistemology. MIT Press.
    The development and deployment of the notion of pre-objective or nonconceptual content for the purposes of intentional explanation of requires assistance from a practical and theoretical understanding of computational/robotic systems acting in real-time and real-space. In particular, the usual "that"-clause specification of content will not work for non-conceptual contents; some other means of specification is required, means that make use of the fact that contents are aspects of embodied and embedded systems. That is, the specification of non-conceptual content should use (...)
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  16. Ronald L. Chrisley (1994). The Ontological Status of Computational States. In European Review of Philosophy, Volume 1: Philosophy of Mind. Stanford: CSLI Publications.
     
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  17. Ronald L. Chrisley (1994). Why Everything Doesn't Realize Every Computation. Minds and Machines 4 (4):403-20.
    Some have suggested that there is no fact to the matter as to whether or not a particular physical system relaizes a particular computational description. This suggestion has been taken to imply that computational states are not real, and cannot, for example, provide a foundation for the cognitive sciences. In particular, Putnam has argued that every ordinary open physical system realizes every abstract finite automaton, implying that the fact that a particular computational characterization applies to a physical system does not (...)
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