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Efficient defeasible reasoning systems
Vancouver, British Columbia, Canada November 13-November 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TAI.2000.88989812th IEEE International Conference on ...
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M.J. Maher, Sch. of Comput. & Inf. Technol., Griffith Univ., Qld., Australia
A. Rock, Sch. of Comput. & Inf. Technol., Griffith Univ., Qld., Australia
G. Antoniou, Sch. of Comput. & Inf. Technol., Griffith Univ., Qld., Australia
D. Billington, Sch. of Comput. & Inf. Technol., Griffith Univ., Qld., Australia
T. Miller, Sch. of Comput. & Inf. Technol., Griffith Univ., Qld., Australia
Abstract: For many years, the non-monotonic reasoning community has focussed on highly expressive logics. Such logics have turned out to be computationally expensive, and have given little support to the practical use of non-monotonic reasoning. In this work we discuss defeasible logic, a less-expressive but more efficient non-monotonic logic. We report on two new implemented systems for defeasible logic: a query answering system employing a backward chaining approach, and a forward-chaining implementation that computes all conclusions. Our experimental evaluation demonstrates that the systems can deal with large theories (up to hundreds of thousands of rules). We show that defeasible logic has linear complexity, which contrasts markedly with most other non-monotonic logics and helps to explain the impressive experimental results. We believe that defeasible logic, with its efficiency and simplicity is a good candidate to be used as a modelling language for practical applications, including modelling of regulations and business rules.
Index Terms:
nonmonotonic reasoning; backward chaining; computational complexity; defeasible reasoning systems; nonmonotonic reasoning; highly expressive logics; query answering system; backward chaining approach; forward-chaining implementation; linear complexity; modelling language; business rules
Citation:
M.J. Maher, A. Rock, G. Antoniou, D. Billington, T. Miller, "Efficient defeasible reasoning systems," ictai, pp.0384, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000
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