We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Abstract— In Evolutionary Robotics (ER), explicitly rewarding for behavioral diversity recently revealed to generate efficient results without recourse to complex fitness funct...
Modeling the behavior of imperfect agents from a small number of observations is a difficult, but important task. In the singleagent decision-theoretic setting, inverse optimal co...
Increasingly, high-assurance applications rely on autonomic systems to respond to changes in their environment. The inherent uncertainty present in the environment of autonomic sy...
Users have a strong tendency toward dismissing security dialogs unthinkingly. Prior research has shown that users' responses to security dialogs become significantly more tho...