We present a learning framework for Markovian decision processes that is based on optimization in the policy space. Instead of using relatively slow gradient-based optimization al...
In work on multiprocessor real-time systems, task scheduling with self-suspensions is a relatively unexplored topic. In this paper, soft real-time sporadic task systems are consid...
A computational agent model for monitoring and control of a virtual human agent’s resources and exhaustion is presented. It models a physically grounded intelligent decision maki...
Open learner models (OLM) enable users to access their learner model to view information about their understanding. Opening the learner model to the learner may increase their perc...
This work is concerned with user perceived privacy and how clients (which we call data subjects here) can be empowered to control their own data consistently with their own intere...