A formal approach to protocols and strategies for (legal) negotiation
Proceedings of the 8th international conference on Artificial intelligence and law
A Defeasible Logic of Policy-Based Intention
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Nonmonotonic Rule Systems on Top of Ontology Layers
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
An algorithm for the induction of defeasible logic theories from databases
ADC '03 Proceedings of the 14th Australasian database conference - Volume 17
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
A model of dynamic resource allocation in workflow systems
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
Temporalised normative positions in defeasible logic
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Using Temporal Consistency to Improve Robot Localisation
RoboCup 2006: Robot Soccer World Cup X
Architecture for Hybrid Robotic Behavior
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
INAP'01 Proceedings of the Applications of prolog 14th international conference on Web knowledge management and decision support
Characterising deadlines in temporal modal defeasible logic
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Dialogue games in defeasible logic
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Modelling behaviour requirements for automatic interpretation, simulation and deployment
SIMPAR'10 Proceedings of the Second international conference on Simulation, modeling, and programming for autonomous robots
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A new non-monotonic logic called clausal defeasible logic (CDL) is defined and explained. CDL is the latest in the family of defeasible logics, which, it is argued, is important for knowledge representation and reasoning. CDL increases the expressive power of defeasible logic by allowing clauses where previous defeasible logics only allowed literals. This greater expressiveness allows the representation of the Lottery Paradox, for example. CDL is well-defined, consistent, and has other desirable properties.