Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
Most of the approaches for dealing with uncertainty in the Semantic Web rely on the principle that this uncertainty is already asserted. In this paper, we propose a new approach t...
For formal verification of hardware Satisfiability Modulo Theory (SMT) solvers are increasingly applied. Today’s state-of-the-art SMT solvers use different techniques like ter...
Abstract. This paper presents a separation-logic framework for reasoning about low-level C code in the presence of virtual memory. We describe ract, generic Isabelle/HOL framework ...
What distinguishes multiagent systems from other software systems is their emphasis on the interactions among autonomous, heterogeneous agents. This paper motivates and characteriz...