Propositional knowledge base revision and minimal change
Artificial Intelligence
Representation results for defeasible logic
ACM Transactions on Computational Logic (TOCL)
A Flexible Framework for Defeasible Logics
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Revising Nonmonotonic Theories: The Case of Defeasible Logic
KI '99 Proceedings of the 23rd Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Defeasible logic with dynamic priorities
International Journal of Intelligent Systems
Argumentation Semantics for Defeasible Logic
Journal of Logic and Computation
Rules and Norms: Requirements for Rule Interchange Languages in the Legal Domain
RuleML '09 Proceedings of the 2009 International Symposium on Rule Interchange and Applications
AICOL-I/IVR-XXIV'09 Proceedings of the 2009 international conference on AI approaches to the complexity of legal systems: complex systems, the semantic web, ontologies, argumentation, and dialogue
Rule-based agents, compliance, and intention reconsideration in defeasible logic
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
Designing for compliance: norms and goals
RuleML'11 Proceedings of the 5th international conference on Rule-based modeling and computing on the semantic web
Norm compliance of rule-based cognitive agents
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Hi-index | 0.00 |
We propose a systematic investigation on how to modify a preference relation in a defeasible logic theory to change the conclusions of the theory itself. We argue that the approach we adopt is applicable to legal reasoning, where users, in general, cannot change facts and rules, but can propose their preferences about the relative strength of the rules. We provide a comprehensive study of the possible combinatorial cases and we identify and analyse the cases where the revision process is successful.