Prioritized conflict handing for logic programs
ILPS '97 Proceedings of the 1997 international symposium on Logic programming
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
Executable declarative business rules and their use in electronic commerce
Proceedings of the 2002 ACM symposium on Applied computing
Delegation logic: A logic-based approach to distributed authorization
ACM Transactions on Information and System Security (TISSEC)
On the Analysis of Regulations using Defeasible Rules
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 6 - Volume 6
DR-NEGOTIATE - A System for Automated Agent Negotiation with Defeasible Logic-Based Strategies
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
DR-BROKERING - A Defeasible Logic-Based System for Semantic Brokering
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
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Defeasible reasoning is a rule-based approach for efficient reasoning with incomplete and inconsistent information. Such reasoning is useful for many applications in the Semantic Web, such as policies and business rules, agent brokering and negotiation, ontology and knowledge merging, etc. However, the syntax of defeasible logic may appear too complex for many users. In this paper we present a graphical authoring tool for defeasible logic rules that acts as a shell for the DR-DEVICE defeasible reasoning system over RDF metadata. The tool helps users to develop a rule base using the OO-RuleML syntax of DR-DEVICE rules, by constraining the allowed vocabulary through analysis of the input RDF namespaces, so that the user does not have to type-in class and property names. Rule visualization follows the tree model of RuleML. The DR-DEVICE reasoning system is implemented on top of the CLIPS production rule system and builds upon an earlier deductive rule system over RDF metadata that also supports derived attribute and aggregate attribute rules.