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Forthcoming articles
  1. Simon D'Alfonso (forthcoming). The Logic of Knowledge and the Flow of Information. Minds and Machines:1-19.
    In this paper I look at Fred Dretske’s account of information and knowledge as developed in Knowledge and The Flow of Information. In particular, I translate Dretske’s probabilistic definition of information to a modal logical framework and subsequently use this to explicate the conception of information and its flow which is central to his account, including the notions of channel conditions and relevant alternatives. Some key products of this task are an analysis of the issue of information closure and an (...)
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  2. Andreas Elpidorou (forthcoming). Review of Robert D. Rupert's Cognitive Systems and the Extended Mind. [REVIEW] Minds and Machines.
  3. Stuart Armstrong, Anders Sandberg & Nick Bostrom (forthcoming). Thinking Inside the Box: Using and Controlling an Oracle AI. Minds and Machines.
  4. Mark Jm Bishop & C. Sdrolia (forthcoming). Rethinking Construction. On Luciano Floridi's 'Against Digital Ontology. Minds and Machines.
  5. Jamie Byrom, Christine Consell, Michael Gorman, Michael Riley & Andrew Wrenn (forthcoming). Think Through History. Minds and Machines.
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  6. Carol Cleland (forthcoming). Effective Procedures and Causal Processes. Minds and Machines.
  7. K. Dautenhahn (forthcoming). Socially Intelligent Agents-Towards a Science of Social Minds. Submitted To. Minds and Machines.
  8. K. Laskey (forthcoming). Quantum Physical Symbol Systems. Submitted to Special Issue Of. Minds and Machines.
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  9. Aran Nayebi (forthcoming). Practical Intractability: A Critique of the Hypercomputation Movement. [REVIEW] Minds and Machines:1-31.
    For over a decade, the hypercomputation movement has produced computational models that in theory solve the algorithmically unsolvable, but they are not physically realizable according to currently accepted physical theories. While opponents to the hypercomputation movement provide arguments against the physical realizability of specific models in order to demonstrate this, these arguments lack the generality to be a satisfactory justification against the construction of any information-processing machine that computes beyond the universal Turing machine. To this end, I present a more (...)
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  10. M. I. T. OpenCourseWare (forthcoming). MIT OpenCourseWare. Minds and Machines.
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  11. Kenneth R. Paap & Derek Partridge (forthcoming). Recursion Isn't Necessary for Human Language Processing: NEAR (Non-Iterative Explicit Alternatives Rule) Grammars Are Superior. Minds and Machines:1-26.
    Language sciences have long maintained a close and supposedly necessary coupling between the infinite productivity of the human language faculty and recursive grammars. Because of the formal equivalence between recursion and non-recursive iteration; recursion, in the technical sense, is never a necessary component of a generative grammar. Contrary to some assertions this equivalence extends to both center-embedded relative clauses and hierarchical parse trees. Inspection of language usage suggests that recursive rule components in fact contribute very little, and likely nothing significant, (...)
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  12. Giuseppe Primiero (forthcoming). A Taxonomy of Errors for Information Systems. Minds and Machines:1-25.
    We provide a full characterization of computational error states for information systems. The class of errors considered is general enough to include human rational processes, logical reasoning, scientific progress and data processing in some functional programming languages. The aim is to reach a full taxonomy of error states by analysing the recovery and processing of data. We conclude by presenting machine-readable checking and resolve algorithms.
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  13. O. Shagrir & I. Pitowsky (forthcoming). The Church-Turing Thesis and Hyper-Computation. Minds and Machines.
  14. Jacopo Tagliabue (forthcoming). Anomalous Monism in a Digital Universe. Minds and Machines:1-12.
    Bermúdez (Philosophy of psychology: a contemporary introduction, Routledge, London, 2005) identifies the “Interface Problem” as the central problem in the philosophy of psychology: how commonsensical psychological explanations can be integrated with lower-level (cognitive, biological, etc.) explanations? In particular, since folk psychology is meant to provide causal explanations on a par with, say, neurobiological explanations, the question of how to understand the relation between the two layers arises naturally. Donald Davidson claimed that the interface problem is actually ill-posed and put forward (...)
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