79 citations · 424 across the 54 of their papers we have counts for
11 papers · 1 filter
Conformal Quantitative Predictive Monitoring of STL Requirements for Stochastic Processes
Francesca Cairoli, Nicola Paoletti, Luca Bortolussi
We consider the problem of predictive monitoring (PM), i.e., predicting at runtime the satisfaction of a desired property from the current system's state. Due to its relevance for…
Analysis of Markov Jump Processes under Terminal Constraints
Michael Backenköhler, Luca Bortolussi, Gerrit Großmann +1
Many probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints. We…
Adversarial Learning of Robust and Safe Controllers for Cyber-Physical Systems
Luca Bortolussi, Francesca Cairoli, Ginevra Carbone +2
We introduce a novel learning-based approach to synthesize safe and robust controllers for autonomous Cyber-Physical Systems and, at the same time, to generate challenging tests. T…
Bounding Mean First Passage Times in Population Continuous-Time Markov Chains
Michael Backenköhler, Luca Bortolussi, Verena Wolf
We consider the problem of bounding mean first passage times for a class of continuous-time Markov chains that captures stochastic interactions between groups of identical agents.…
Policy learning for time-bounded reachability in Continuous-Time Markov Decision Processes via doubly-stochastic gradient ascent
Ezio Bartocci, Luca Bortolussi, Tomǎš Brázdil +2
Continuous-time Markov decision processes are an important class of models in a wide range of applications, ranging from cyber-physical systems to synthetic biology. A central prob…
Learning and Designing Stochastic Processes from Logical Constraints
Luca Bortolussi, Guido Sanguinetti
Stochastic processes offer a flexible mathematical formalism to model and reason about systems. Most analysis tools, however, start from the premises that models are fully specifie…
Stochastic HYPE: Flow-based modelling of stochastic hybrid systems
Luca Bortolussi, Vashti Galpin, Jane Hillston
Stochastic HYPE is a novel process algebra that models stochastic, instantaneous and continuous behaviour. It develops the flow-based approach of the hybrid process algebra HYPE by…
Mean-Field approximation and Quasi-Equilibrium reduction of Markov Population Models
Luca Bortolussi, Rytis Paškauskas
Markov Population Model is a commonly used framework to describe stochastic systems. Their exact analysis is unfeasible in most cases because of the state space explosion. Approxim…
Proceedings Third International Workshop on Hybrid Autonomous Systems
Luca Bortolussi, Manuela L. Bujorianu, Giordano Pola
The interest on autonomous systems is increasing both in industry and academia. Such systems must operate with limited human intervention in a changing environment and must be able…
Hybrid Behaviour of Markov Population Models
Luca Bortolussi
We investigate the behaviour of population models written in Stochastic Concurrent Constraint Programming (sCCP), a stochastic extension of Concurrent Constraint Programming. In pa…
Hybrid performance modelling of opportunistic networks
Luca Bortolussi, Vashti Galpin, Jane Hillston
We demonstrate the modelling of opportunistic networks using the process algebra stochastic HYPE. Network traffic is modelled as continuous flows, contact between nodes in the netw…