Constraints and quantitative preferences, or costs, are very useful for modelling many real-life problems. However, in many settings, it is difficult to specify precise preference ...
Mirco Gelain, Maria Silvia Pini, Francesca Rossi, ...
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Self-assessment motivation questionnaires have been used in classrooms yet many researchers find only a weak correlation between answers to these questions and learning. In this pa...
—We analyze a comprehensive model for multi-class job scheduling accounting for user abandonment, with the objective of minimizing the total discounted or time-average sum of lin...
The improvements of the luminosity of the Tevatron Collider require large increases in computing requirements for the CDF experiment which has to be able to increase proportionally...