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...
Robust execution of robotic tasks is a difficult problem. In many situations, these tasks involve complex behaviors combining different functionalities (e.g. perception, localizat...
Abstract. Our research group has analyzed many industrial, frameworkbased applications. In these applications, simple functionality often requires excessive runtime activity. It is...
We solve a longstanding problem by providing a denotational model for nondeterministic programs that identifies two programs iff they have the same range of possible behaviours. W...
Programs typically make extensive use of libraries, including dynamically linked libraries, which are often not available in source-code form, and hence not analyzable by tools tha...