6 found
Timothy R. Colburn [6]Timothy Robert Colburn [1]
  1. Software, Abstraction, and Ontology.Timothy R. Colburn - 1999 - The Monist 82 (1):3-19.
    This paper analyzes both philosophical and practical assumptions underlying claims for the dual nature of software, including software as a machine made of text, and software as a concrete abstraction. A related view of computer science as a branch of pure mathematics is analyzed through a comparative examination of the nature of abstraction in mathematics and computer science. The relationship between the concrete and the abstract in computer programs is then described by exploring a taxonomy of approaches borrowed from philosophy (...)
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    Program verification, defeasible reasoning, and two views of computer science.Timothy R. Colburn - 1991 - Minds and Machines 1 (1):97-116.
    In this paper I attempt to cast the current program verification debate within a more general perspective on the methodologies and goals of computer science. I show, first, how any method involved in demonstrating the correctness of a physically executing computer program, whether by testing or formal verification, involves reasoning that is defeasible in nature. Then, through a delineation of the senses in which programs can be run as tests, I show that the activities of testing and formal verification do (...)
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    Books for review and for listing here should be addressed to Emily Zakin, Review Editor, Teaching Philosophy, Department of Philosophy, Miami University, Oxford, OH 45056.Robert Almeder, Lynne Rudder Baker, José Luis Bermúdez, James Robert Brown, Jeremy Butterfield, Constantine Pagonis, Steven M. Cahn, John D. Caputo, J. Michael & Timothy R. Colburn - 2000 - Teaching Philosophy 23 (2):227.
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    Defeasible reasoning and logic programming.Timothy R. Colburn - 1991 - Minds and Machines 1 (4):417-436.
    The general conditions of epistemic defeat are naturally represented through the interplay of two distinct kinds of entailment, deductive and defeasible. Many of the current approaches to modeling defeasible reasoning seek to define defeasible entailment via model-theoretic notions like truth and satisfiability, which, I argue, fails to capture this fundamental distinction between truthpreserving and justification-preserving entailments. I present an alternative account of defeasible entailment and show how logic programming offers a paradigm in which the distinction can be captured, allowing for (...)
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    Heuristics, justification, and defeasible reasoning.Timothy R. Colburn - 1995 - Minds and Machines 5 (4):467-487.
    Heuristics can be regarded as justifying the actions and beliefs of problem-solving agents. I use an analysis of heuristics to argue that a symbiotic relationship exists between traditional epistemology and contemporary artificial intelligence. On one hand, the study of models of problem-solving agents usingquantitative heuristics, for example computer programs, can reveal insight into the understanding of human patterns of epistemic justification by evaluating these models'' performance against human problem-solving. On the other hand,qualitative heuristics embody the justifying ability of defeasible rules, (...)
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    Information modeling aspects of software development.Timothy R. Colburn - 1998 - Minds and Machines 8 (3):375-393.
    The distinction between the modeling of information and the modeling of data in the creation of automated systems has historically been important because the development tools available to programmers have been wedded to machine oriented data types and processes. However, advances in software engineering, particularly the move toward data abstraction in software design, allow activities reasonably described as information modeling to be performed in the software creation process. An examination of the evolution of programming languages and development of general programming (...)
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