27 citations · 59 across the 21 of their papers we have counts for
23 papers
Towards Agentic Agent-based Models: Feasibility, Performance, and Statistical Model Checking
Stefano Blando, Emanuele Guerrazzi, Riccardo Porcedda +3
Agent-based models (ABMs) rely on simple, explicit and reproducible rules for individual decision making, while complex collective behavior emerges from interactions among agents.…
Constrained Quantum Optimization meets Model Reduction
Max Tschaikowski, Andrea Vandin
Quantum optimization algorithms promise advantages for difficult problems but are costly to simulate and analyze on classical machines. Recently, constrained quantum optimization h…
Approximate Constrained Lumping of Chemical Reaction Networks
Alexander Leguizamon-Robayo, Antonio Jiménez-Pastor, Micro Tribastone +2
Gaining insights from realistic dynamical models of biochemical systems can be challenging given their large number of state variables. Model reduction techniques can mitigate this…
Efficient Network Embedding by Approximate Equitable Partitions
Giuseppe Squillace, Mirco Tribastone, Max Tschaikowski +1
Structural network embedding is a crucial step in enabling effective downstream tasks for complex systems that aims to project a network into a lower-dimensional space while preser…
Accurate and fast anomaly detection in industrial processes and IoT environments
Simone Tonini, Andrea Vandin, Francesca Chiaromonte +2
We present a novel, simple and widely applicable semi-supervised procedure for anomaly detection in industrial and IoT environments, SAnD (Simple Anomaly Detection). SAnD comprises…
White-box validation of quantitative product lines by statistical model checking and process mining
Roberto Casaluce, Andrea Burattin, Francesca Chiaromonte +2
We propose a novel methodology for validating software product line (PL) models by integrating Statistical Model Checking (SMC) with Process Mining (PM). Our approach focuses on th…
Proper Lumping for Positive Bilinear Control Systems
Antonio Jiménez-Pastor, Daniele Toller, Mirco Tribastone +2
Positive systems naturally arise in situations where the model tracks physical quantities. Although the linear case is well understood, analysis and controller design for nonlinear…
Coarse-graining Complex Networks for Control Equivalence
Daniele Toller, Mirco Tribastone, Max Tschaikowski +1
The ability to control complex networks is of crucial importance across a wide range of applications in natural and engineering sciences. However, issues of both theoretical and nu…
Optimality-preserving Reduction of Chemical Reaction Networks
Kim G. Larsen, Daniele Toller, Mirco Tribastone +2
Across many disciplines, chemical reaction networks (CRNs) are an established population model defined as a system of coupled nonlinear ordinary differential equations. In many app…
Minimization of Dynamical Systems over Monoids
Georgios Argyris, Alberto Lluch Lafuente, Alexander Leguizamon Robayo +3
Quantitative notions of bisimulation are well-known tools for the minimization of dynamical models such as Markov chains and ordinary differential equations (ODEs). In \emph{forwar…
Formal Analysis of Lending Pools in Decentralized Finance
Massimo Bartoletti, James Chiang, Tommi Junttila +3
Decentralised Finance (DeFi) applications constitute an entire financial ecosystem deployed on blockchains. Such applications are based on complex protocols and incentive mechanism…
Reducing Boolean Networks with Backward Boolean Equivalence
Georgios Argyris, Alberto Lluch Lafuente, Mirco Tribastone +2
Boolean Networks (BNs) are established models to qualitatively describe biological systems. The analysis of BNs might be infeasible for medium to large BNs due to the state-space e…
Efficient Local Computation of Differential Bisimulations via Coupling and Up-to Methods
Giorgio Bacci, Giovanni Bacci, Kim G. Larsen +3
We introduce polynomial couplings, a generalization of probabilistic couplings, to develop an algorithm for the computation of equivalence relations which can be interpreted as a l…
Automated and Distributed Statistical Analysis of Economic Agent-Based Models
Andrea Vandin, Daniele Giachini, Francesco Lamperti +1
We propose a novel approach to the statistical analysis of stochastic simulation models and, especially, agent-based models (ABMs). Our main goal is to provide fully automated, mod…
Quantitative Security Risk Modeling and Analysis with RisQFLan
Maurice H. ter Beek, Axel Legay, Alberto Lluch Lafuente +1
Domain-specific quantitative modeling and analysis approaches are fundamental in scenarios in which qualitative approaches are inappropriate or unfeasible. In this paper, we presen…
Exact maximal reduction of stochastic reaction networks by species lumping
Luca Cardelli, Isabel Cristina Perez-Verona, Mirco Tribastone +3
Motivation: Stochastic reaction networks are a widespread model to describe biological systems where the presence of noise is relevant, such as in cell regulatory processes. Unfort…
Improved estimations of stochastic chemical kinetics by finite state expansion
Tabea Waizmann, Luca Bortolussi, Andrea Vandin +1
Stochastic reaction networks are a fundamental model to describe interactions between species where random fluctuations are relevant. The master equation provides the evolution of…
Guaranteed Error Bounds on Approximate Model Abstractions through Reachability Analysis
Luca Cardelli, Mirco Tribastone, Max Tschaikowski +1
It is well known that exact notions of model abstraction and reduction for dynamical systems may not be robust enough in practice because they are highly sensitive to the specific…
Language-based Abstractions for Dynamical Systems
Andrea Vandin
Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a…
Syntactic Markovian Bisimulation for Chemical Reaction Networks
Luca Cardelli, Mirco Tribastone, Max Tschaikowski +1
In chemical reaction networks (CRNs) with stochastic semantics based on continuous-time Markov chains (CTMCs), the typically large populations of species cause combinatorially larg…
A framework for quantitative modeling and analysis of highly (re)configurable systems
Maurice H. ter Beek, Axel Legay, Alberto Lluch Lafuente +1
This paper presents our approach to the quantitative modeling and analysis of highly (re)configurable systems, such as software product lines. Different combinations of the optiona…
Forward and Backward Bisimulations for Chemical Reaction Networks
Luca Cardelli, Mirco Tribastone, Max Tschaikowski +1
We present two quantitative behavioral equivalences over species of a chemical reaction network (CRN) with semantics based on ordinary differential equations. Forward CRN bisimulat…
Quantitative Analysis of Probabilistic Models of Software Product Lines with Statistical Model Checking
Maurice H. ter Beek, Axel Legay, Alberto Lluch Lafuente +1
We investigate the suitability of statistical model checking techniques for analysing quantitative properties of software product line models with probabilistic aspects. For this p…