Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
—In this paper, we present a UML metamodel-based approach for creating and executing workflow models. The modeling language is introduced through its abstract syntax, and an eval...
Parameterized model checking refers to any method that extends traditional, finite-state model checking to handle systems arbitrary number of processes. One popular approach to thi...
Abstract. A needle-tissue interaction model is an essential part of every needle insertion simulator. In this paper, a new experimental method for the modeling of needle-tissue int...
Abstract. There is little doubt that intelligent and adaptive educational technologies are capable of providing personalized learning experiences and improving learning success. Cu...