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  1. 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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  2. Derek Partridge (1995). On the Difficulty of Really Considering a Radical Novelty. Minds and Machines 5 (3):391-410.
    The fundamental assumptions in Dijkstra''s influential article on computing science teaching are challenged. Dijkstra''s paper presents the radical novelties of computing, and the consequent problems that we must tackle through a formal, logic-based approach to program derivation. Dijkstra''s main premise is that the algorithmic programming paradigm is the only one, in fact, the only possible one. It is argued that there is at least one other, the network-programming paradigm, which itself is a radical novelty with respect to the implementation of (...)
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  3. Derek Partridge & Antony Galton (1995). The Specification of “Specification”. Minds and Machines 5 (2):243-255.
    The notion of specification plays a key role in the developing science of computing. It is typically considered to be the keystone in the software development process. However, there is no single, generally agreed meaning of specification that bears close scrutiny. Instead there is a variety of different, although partially interlocking and overlapping interpretations of the term.We catalogue this varietal profusion and attempt to lay bare both the sources and consequences of each major alternative. We attempt to present the full (...)
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  4. Derek Partridge & Y. Wilks (eds.) (1990). The Foundations of Artificial Intelligence: A Sourcebook. Cambridge University Press.
    This outstanding collection is designed to address the fundamental issues and principles underlying the task of Artificial Intelligence.
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  5. Derek Partridge (1987). Human Decision Making & the Symbolic Search Space Paradigm in AI. AI and Society 1 (2):103-114.
    In this paper I shall describe the symbolic search space paradigm which is the dominant model for most of AI. Coupled with the mechanisms of logic it yields the predominant methodology underlying expert systems which are the most successful application of AI technology to date. Human decision making, more precisely, expert human decision making is the function that expert systems aspire to emulate, if not surpass.Expert systems technology has not yet proved to be a decisive success — it appears to (...)
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  6. Arthur I. Karshmer, Derek Partridge & Victor Johnson (1982). Exploratory Behavior Without Novelty Drive? Behavioral and Brain Sciences 5 (4):644.
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  7. Derek Partridge (1981). Information Theory and Redundancy. Philosophy of Science 48 (2):308-316.
    This paper argues that Information Theoretic Redundancy (ITR) is fundamentally a composite concept that has been continually misinterpreted since the very inception of Information Theory. We view ITR as compounded of true redundancy and partial redundancy. This demarcation of true redundancy illustrates a limiting case phenomenon: the underlying metric (number of alternatives) differs only by degree but the properties of this concept differ in kind from those of partial redundancy. Several other studies are instanced which also imply the composite nature (...)
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