Representation results for defeasible logic
ACM Transactions on Computational Logic (TOCL)
A formal approach to protocols and strategies for (legal) negotiation
Proceedings of the 8th international conference on Artificial intelligence and law
Embedding Defeasible Logic into Logic Programs
ICLP '02 Proceedings of the 18th International Conference on Logic Programming
Relating Defeasible Logic to Extended Logic Programs
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Relating Defeasible and Default Logic
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
On the Relationship between Defeasible Logic and Well-Founded Semantics
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
Propositional defeasible logic has linear complexity
Theory and Practice of Logic Programming
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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.