On the logic of iterated belief revision
Artificial Intelligence
Autonomous Agents and Multi-Agent Systems
On the revision of preferences and rational inference processes
Artificial Intelligence
Dynamic Epistemic Logic
Defining relative likelihood in partially-ordered preferential structures
Journal of Artificial Intelligence Research
Hidden uncertainty in the logical representation of desires
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Preference change triggered by belief change: a principled approach
LOFT'08 Proceedings of the 8th international conference on Logic and the foundations of game and decision theory
Increasing users' trust on personal assistance software using a domain-neutral high-level user model
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
Actions, preferences, and logic programs
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
Revision over partial pre-orders: a postulational study
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
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Various tasks need to consider preferences in a dynamic way. We start by discussing several possible meanings of preference change, and then focus on the one we think is the most natural: preferences evolving after some new fact has been learned. We define a family of such preference change operators, parameterized by a revision function on epistemic states and a semantics for interpreting preferences over formulas. We list some natural properties that this kind of preference change should fulfill and give conditions on the revision function and the semantics of preference for each of these properties to hold.