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pro vyhledávání: '"LORETI, MICHELE"'
Graph neural networks form a class of deep learning architectures specifically designed to work with graph-structured data. As such, they share the inherent limitations and problems of deep learning, especially regarding the issues of explainability
Externí odkaz:
http://arxiv.org/abs/2407.09441
WebAssembly is a binary format for code that is gaining popularity thanks to its focus on portability and performance. Currently, the most common use case for WebAssembly is execution in a browser. It is also being increasingly adopted as a stand-alo
Externí odkaz:
http://arxiv.org/abs/2407.14527
We propose the Robustness Temporal Logic (RobTL), a novel temporal logic for the specification and analysis of distances between the behaviours of Cyber-Physical Systems (CPSs) over a finite time horizon. Differently from classical temporal logic exp
Externí odkaz:
http://arxiv.org/abs/2212.11158
Publikováno v:
In Theoretical Computer Science 29 December 2024 1022
The behaviour of systems characterised by a closed interaction of software components with the environment is inevitably subject to perturbations and uncertainties. In this paper we propose a general framework for the specification and verification o
Externí odkaz:
http://arxiv.org/abs/2204.13357
Publikováno v:
Logical Methods in Computer Science, Volume 19, Issue 3 (July 7, 2023) lmcs:8780
Due to the diffusion of IoT, modern software systems are often thought to control and coordinate smart devices in order to manage assets and resources, and to guarantee efficient behaviours. For this class of systems, which interact extensively with
Externí odkaz:
http://arxiv.org/abs/2111.15319
From biological systems to cyber-physical systems, monitoring the behavior of such dynamical systems often requires to reason about complex spatio-temporal properties of physical and/or computational entities that are dynamically interconnected and a
Externí odkaz:
http://arxiv.org/abs/2109.08081
Autor:
Loreti, Michele, Quadrini, Michela
Publikováno v:
Logical Methods in Computer Science, Volume 19, Issue 3 (July 26, 2023) lmcs:8576
Collective Adaptive Systems often consist of many heterogeneous components typically organised in groups. These entities interact with each other by adapting their behaviour to pursue individual or collective goals. In these systems, the distribution
Externí odkaz:
http://arxiv.org/abs/2105.08708
We present MoonLight, a tool for monitoring temporal and spatio-temporal properties of mobile and spatially distributed cyber-physical systems (CPS). In the proposed framework, space is represented as a weighted graph, describing the topological conf
Externí odkaz:
http://arxiv.org/abs/2104.14333
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