Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Complex student models often include key parameters critical to their behavior and effectiveness. For example, one meta-cognitive model of student help-seeking in intelligent tutor...
Benjamin Shih, Kenneth R. Koedinger, Richard Schei...
This paper proposes a new planning architecture for agents operating in uncertain and dynamic environments. Decisiontheoretic planning has been recognized as a useful tool for rea...
Model-Driven Architecture is an approach of the OMG, its objective is to tackle problems such as: the high availability that a software product requires to be ready for use, the h...
In this paper we present pddl+, a planning domain description language for modelling mixed discrete-continuous planning domains. We describe the syntax and modelling style of pddl...