Abstract. We axiomatically characterise a class of algorithms for making sequential decisions in situations of complete ignorance. These algorithms assume that a decision maker (DM...
User preferences for automated assistance often vary widely, depending on the situation, and quality or presentation of help. Developing effective models to learn individual prefe...
To create a robot with a mind of its own, we extended a formalized version of a model that explains affect-driven interaction with mechanisms for goaldirected behavior. We ran sim...
Johan F. Hoorn, Matthijs Pontier, Ghazanfar F. Sid...
Reputation mechanisms offer an efficient way of building the necessary level of trust in electronic markets. Feedback about an agent’s past behavior can be aggregated into a me...
In previous work [8] we presented a casebased approach to eliciting and reasoning with preferences. A key issue in this approach is the definition of similarity between user prefe...