14 found
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  1.  58
    A Formal Analysis of Relevance.James P. Delgrande & Francis Jeffry Pelletier - 1998 - Erkenntnis 49 (2):137-173.
    We investigate the notion of relevance as it pertains to ‘commonsense’, subjunctive conditionals. Relevance is taken here as a relation between a property (such as having a broken wing) and a conditional (such as birds typically fly). Specifically, we explore a notion of ‘causative’ relevance, distinct from ‘evidential’ relevance found, for example, in probabilistic approaches. A series of postulates characterising a minimal, parsimonious concept of relevance is developed. Along the way we argue that no purely logical account of relevance (even (...)
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  2.  59
    Gricean Belief Change.James P. Delgrande, Abhaya C. Nayak & Maurice Pagnucco - 2005 - Studia Logica 79 (1):97-113.
    One of the standard principles of rationality guiding traditional accounts of belief change is the principle of minimal change: a reasoner's belief corpus should be modified in a minimal fashion when assimilating new information. This rationality principle has stood belief change in good stead. However, it does not deal properly with all belief change scenarios. We introduce a novel account of belief change motivated by one of Grice's maxims of conversational implicature: the reasoner's belief corpus is modified in a minimal (...)
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  3.  12
    A Consistency-Based Framework for Merging Knowledge Bases.James P. Delgrande & Torsten Schaub - 2007 - Journal of Applied Logic 5 (3):459-477.
  4. Alternative Approaches to Default Logic.James P. Delgrande, Torsten Schaub & W. Ken Jackson - 1994 - Artificial Intelligence 70 (1-2):167-237.
  5. An Approach to Default Reasoning Based on a First-Order Conditional Logic: Revised Report.James P. Delgrande - 1988 - Artificial Intelligence 36 (1):63-90.
  6. A Consistency-Based Approach for Belief Change.James P. Delgrande & Torsten Schaub - 2003 - Artificial Intelligence 151 (1-2):1-41.
  7.  13
    An Epistemic Approach to Nondeterminism: Believing in the Simplest Course of Events.James P. Delgrande & Hector J. Levesque - 2019 - Studia Logica 107 (5):859-886.
    This paper describes an approach for reasoning in a dynamic domain with nondeterministic actions in which an agent’s beliefs correspond to the simplest, or most plausible, course of events consistent with the agent’s observations and beliefs. The account is based on an epistemic extension of the situation calculus, a first-order theory of reasoning about action that accommodates sensing actions. In particular, the account is based on a qualitative theory of nondeterminism. Our position is that for commonsense reasoning, the world is (...)
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  8. A First-Order Conditional Logic for Prototypical Properties.James P. Delgrande - 1987 - Artificial Intelligence 33 (1):105-130.
  9. Belief Revision in Horn Theories.James P. Delgrande & Pavlos Peppas - 2015 - Artificial Intelligence 218:1-22.
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  10. Compiling Specificity Into Approaches to Nonmonotonic Reasoning.James P. Delgrande & Torsten H. Schaub - 1997 - Artificial Intelligence 90 (1-2):301-348.
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  11. Expressing Preferences in Default Logic.James P. Delgrande & Torsten Schaub - 2000 - Artificial Intelligence 123 (1-2):41-87.
  12. On First-Order Conditional Logics.James P. Delgrande - 1998 - Artificial Intelligence 105 (1-2):105-137.
  13.  46
    Reasoning Credulously and Skeptically Within a Single Extension.James P. Delgrande & Torsten Schaub - 2002 - Journal of Applied Non-Classical Logics 12 (2):259-285.
    Consistency-based approaches in nonmonotonic reasoning may be expected to yield multiple sets of default conclusions for a given default theory. Reasoning about such extensions is carried out at the meta-level. In this paper, we show how such reasoning may be carried out at the object level for a large class of default theories. Essentially we show how one can translate a default theory Δ, obtaining a second Δ', such that Δ has a single extension that encodes every extension of _. (...)
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  14.  3
    The Logic of Qualitative Probability.James P. Delgrande, Bryan Renne & Joshua Sack - 2019 - Artificial Intelligence 275:457-486.
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