The concept of features provides an elegant way to specify families of systems. Given a base
system, features encapsulate additional functionalities that can be activated or deactivated …

Markov models comprise states with probabilistic transitions. The analysis of these models is
ubiquitous and studied in, among others, reliability engineering, artificial intelligence …

With the explosion of the number of compute nodes, the bottleneck of future computing
systems lies in the network architecture connecting the nodes. Addressing the bottleneck …

We consider the verification of multiple expected reward objectives at once on Markov
decision processes (MDPs). This enables a trade-off analysis among multiple objectives by …

This paper presents a retrospective view on probabilistic model checking. We focus on
Markov decision processes (MDPs, for short). We survey the basic ingredients of MDP …

Abstract Given Markov chains and Markov decision processes (MDPs) whose transitions are
labelled with non-negative integer costs, we study the computational complexity of deciding …

The popular model checker PRISM has been successfully used for the modeling and
analysis of complex probabilistic systems. As one way to tackle the challenging state …

We provide a memory-efficient algorithm for multi-objective model checking problems on
Markov decision processes (MDPs) with multiple cost structures. The key problem at hand is …

Plenty of novel emerging technologies are being proposed and evaluated today, mostly at
the device and circuit levels. It is unclear what the impact of different new technologies at the …

Markov decision processes (MDPs) with multi-dimensional weights are useful to analyze
systems with multiple objectives that may be conflicting and require the analysis of trade …