Switch to: Citations

Add references

You must login to add references.
  1. A mathematical treatment of defeasible reasoning and its implementation.Guillermo R. Simari & Ronald P. Loui - 1992 - Artificial Intelligence 53 (2-3):125-157.
    We present a mathematical approach to defeasible reasoning based on arguments. This approach integrates the notion of specificity introduced by Poole and the theory of warrant presented by Pollock. The main contribution of this paper is a precise, well-defined system which exhibits correct behavior when applied to the benchmark examples in the literature. It aims for usability rather than novelty. We prove that an order relation can be introduced among equivalence classes of arguments under the equi-specificity relation. We also prove (...)
    Download  
     
    Export citation  
     
    Bookmark   78 citations  
  • A logic for default reasoning.Ray Reiter - 1980 - Artificial Intelligence 13 (1-2):81-137.
    Download  
     
    Export citation  
     
    Bookmark   634 citations  
  • On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games.Phan Minh Dung - 1995 - Artificial Intelligence 77 (2):321-357.
    Download  
     
    Export citation  
     
    Bookmark   445 citations  
  • Argument-based extended logic programming with defeasible priorities.Henry Prakken & Giovanni Sartor - 1997 - Journal of Applied Non-Classical Logics 7 (1-2):25-75.
    ABSTRACT Inspired by legal reasoning, this paper presents a semantics and proof theory of a system for defeasible argumentation. Arguments are expressed in a logic-programming language with both weak and strong negation, conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that these priorities are not fixed, but are themselves defeasibly derived as conclusions within the system. Thus debates on the choice between conflicting arguments can also be modelled. The (...)
    Download  
     
    Export citation  
     
    Bookmark   87 citations  
  • The logical foundations of goal-regression planning in autonomous agents.John L. Pollock - 1998 - Artificial Intelligence 106 (2):267-334.
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • Perceiving and reasoning about a changing world.John Pollock - unknown
    A rational agent (artificial or otherwise) residing in a complex changing environment must gather information perceptually, update that information as the world changes, and combine that information with causal information to reason about the changing world. Using the system of defeasible reasoning that is incorporated into the OSCAR architecture for rational agents, a set of reasonschemas is proposed for enabling an agent to perform some of the requisite reasoning. Along the way, solutions are proposed for the Frame Problem, the Qualification (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • Justification and defeat.John L. Pollock - 1994 - Artificial Intelligence 67 (2):377-407.
    Download  
     
    Export citation  
     
    Bookmark   45 citations  
  • How to reason defeasibly.John L. Pollock - 1992 - Artificial Intelligence 57 (1):1-42.
    Download  
     
    Export citation  
     
    Bookmark   60 citations  
  • ``Defeasible Reasoning with Variable Degrees of Justification".John L. Pollock - 2001 - Artificial Intelligence 133 (1-2):233-282.
    The question addressed in this paper is how the degree of justification of a belief is determined. A conclusion may be supported by several different arguments, the arguments typically being defeasible, and there may also be arguments of varying strengths for defeaters for some of the supporting arguments. What is sought is a way of computing the “on sum” degree of justification of a conclusion in terms of the degrees of justification of all relevant premises and the strengths of all (...)
    Download  
     
    Export citation  
     
    Bookmark   43 citations  
  • Floating conclusions and zombie paths: Two deep difficulties in the “directly skeptical” approach to defeasible inheritance nets.David Makinson & Karl Schlechta - 1991 - Artificial Intelligence 48 (2):199-209.
    Download  
     
    Export citation  
     
    Bookmark   26 citations  
  • Skepticism and floating conclusions.John F. Horty - 2002 - Artificial Intelligence 135 (1-2):55-72.
    Download  
     
    Export citation  
     
    Bookmark   19 citations  
  • Extending abstract argumentation systems theory.P. Baroni, M. Giacomin & G. Guida - 2000 - Artificial Intelligence 120 (2):251-270.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Artificial argument assistants for defeasible argumentation.Bart Verheij - 2003 - Artificial Intelligence 150 (1-2):291-324.
    Download  
     
    Export citation  
     
    Bookmark   26 citations  
  • Abstract argumentation systems.Gerard A. W. Vreeswijk - 1997 - Artificial Intelligence 90 (1-2):225-279.
    Download  
     
    Export citation  
     
    Bookmark   61 citations