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  1. Article ; Online: BUSTLE: a Versatile Tool for the Evolutionary Learning of STL Specifications from Data.

    Pigozzi, Federico / Nenzi, Laura / Medvet, Eric

    Evolutionary computation

    2024  , Page(s) 1–24

    Abstract: Describing the properties of complex systems that evolve over time is a crucial requirement for monitoring and understanding them. Signal Temporal Logic (STL) is a framework that proved to be effective for this aim because it is expressive and allows ... ...

    Abstract Describing the properties of complex systems that evolve over time is a crucial requirement for monitoring and understanding them. Signal Temporal Logic (STL) is a framework that proved to be effective for this aim because it is expressive and allows state properties as human-readable formulae. Crafting STL formulae that fit a particular system is, however, a difficult task. For this reason, a few approaches have been proposed recently for the automatic learning of STL formulae starting from observations of the system. In this paper, we propose BUSTLE (Bi-level Universal STL Evolver), an approach based on evolutionary computation for learning STL formulae from data. BUSTLE advances the state-of-the-art because it (i) applies to a broader class of problems, in terms of what is known about the state of the system during its observation, and (ii) generates both the structure and the values of the parameters of the formulae employing a bi-level search mechanism (global for the structure, local for the parameters). We consider two cases where (a) observations of the system in both anomalous and regular state are available, or (b) only observations of regular state are available. We experimentally evaluate BUSTLE on problem instances corresponding to the two cases and compare it against previous approaches. We show that the evolved STL formulae are effective and human-readable: the versatility of BUSTLE does not come at the cost of lower effectiveness.
    Language English
    Publishing date 2024-02-19
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2022147-2
    ISSN 1530-9304 ; 1530-9304
    ISSN (online) 1530-9304
    ISSN 1530-9304
    DOI 10.1162/evco_a_00347
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: MoonLight

    Bartocci, Ezio / Bortolussi, Luca / Nenzi, Laura / Silvetti, Simone

    A Lightweight Tool for Monitoring Spatio-Temporal Properties

    2021  

    Abstract: 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 ... ...

    Abstract 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 configurations in which the single CPS entities (nodes of the graph) are arranged. Both nodes and edges have attributes modelling physical and logical quantities that can change in time. MoonLight is implemented in Java and supports the monitoring of Spatio-Temporal Reach and Escape Logic (STREL). MoonLight can be used as a standalone command line tool, as a Java API, or via Matlab interface. We provide here some examples using the Matlab interface and we evaluate the tool performance also by comparing with other tools specialized in monitoring only temporal properties.

    Comment: 12 pages, 6 figures
    Keywords Computer Science - Logic in Computer Science
    Publishing date 2021-04-29
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: Online Monitoring of Spatio-Temporal Properties for Imprecise Signals

    Visconti, Ennio / Bartocci, Ezio / Loreti, Michele / Nenzi, Laura

    2021  

    Abstract: 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 ... ...

    Abstract 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 arranged in a particular spatial configuration. Spatio-Temporal Reach and Escape Logic (STREL) is a recent logic-based formal language designed to specify and to reason about spatio-temporal properties. STREL considers each system's entity as a node of a dynamic weighted graph representing their spatial arrangement. Each node generates a set of mixed-analog signals describing the evolution over time of computational and physical quantities characterising the node's behavior. While there are offline algorithms available for monitoring STREL specifications over logged simulation traces, here we investigate for the first time an online algorithm enabling the runtime verification during the system's execution or simulation. Our approach extends the original framework by considering imprecise signals and by enhancing the logics' semantics with the possibility to express partial guarantees about the conformance of the system's behavior with its specification. Finally, we demonstrate our approach in a real-world environmental monitoring case study.
    Keywords Computer Science - Logic in Computer Science
    Subject code 004
    Publishing date 2021-09-16
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Mining Interpretable Spatio-temporal Logic Properties for Spatially Distributed Systems

    Mohammadinejad, Sara / Deshmukh, Jyotirmy V. / Nenzi, Laura

    2021  

    Abstract: The Internet-of-Things, complex sensor networks, multi-agent cyber-physical systems are all examples of spatially distributed systems that continuously evolve in time. Such systems generate huge amounts of spatio-temporal data, and system designers are ... ...

    Abstract The Internet-of-Things, complex sensor networks, multi-agent cyber-physical systems are all examples of spatially distributed systems that continuously evolve in time. Such systems generate huge amounts of spatio-temporal data, and system designers are often interested in analyzing and discovering structure within the data. There has been considerable interest in learning causal and logical properties of temporal data using logics such as Signal Temporal Logic (STL); however, there is limited work on discovering such relations on spatio-temporal data. We propose the first set of algorithms for unsupervised learning for spatio-temporal data. Our method does automatic feature extraction from the spatio-temporal data by projecting it onto the parameter space of a parametric spatio-temporal reach and escape logic (PSTREL). We propose an agglomerative hierarchical clustering technique that guarantees that each cluster satisfies a distinct STREL formula. We show that our method generates STREL formulas of bounded description complexity using a novel decision-tree approach which generalizes previous unsupervised learning techniques for Signal Temporal Logic. We demonstrate the effectiveness of our approach on case studies from diverse domains such as urban transportation, epidemiology, green infrastructure, and air quality monitoring.
    Keywords Computer Science - Machine Learning
    Subject code 006
    Publishing date 2021-06-16
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: A kernel function for Signal Temporal Logic formulae

    Bortolussi, Luca / Gallo, Giuseppe Maria / Nenzi, Laura

    2020  

    Abstract: We discuss how to define a kernel for Signal Temporal Logic (STL) formulae. Such a kernel allows us to embed the space of formulae into a Hilbert space, and opens up the use of kernel-based machine learning algorithms in the context of STL. We show an ... ...

    Abstract We discuss how to define a kernel for Signal Temporal Logic (STL) formulae. Such a kernel allows us to embed the space of formulae into a Hilbert space, and opens up the use of kernel-based machine learning algorithms in the context of STL. We show an application of this idea to a regression problem in formula space for probabilistic models.

    Comment: 12 pages, 3 figures
    Keywords Computer Science - Machine Learning ; Computer Science - Logic in Computer Science ; Statistics - Machine Learning
    Publishing date 2020-09-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  6. Book ; Online: Posterior predictive model checking using formal methods in a spatio-temporal model

    Vana, Laura / Visconti, Ennio / Nenzi, Laura / Cadonna, Annalisa / Kastner, Gregor

    2021  

    Abstract: We propose an interdisciplinary framework, Bayesian formal predictive model checking (Bayes FPMC), which combines Bayesian predictive inference, a well established tool in statistics, with formal verification methods rooting in the computer science ... ...

    Abstract We propose an interdisciplinary framework, Bayesian formal predictive model checking (Bayes FPMC), which combines Bayesian predictive inference, a well established tool in statistics, with formal verification methods rooting in the computer science community. Bayesian predictive inference allows for coherently incorporating uncertainty about unknown quantities by making use of methods or models that produce predictive distributions which in turn inform decision problems. By formalizing these problems and the corresponding properties, we can use spatio-temporal reach and escape logic to probabilistically assess their satisfaction. This way, competing models can directly be ranked according to how well they solve the actual problem at hand. The approach is illustrated on an urban mobility application, where the crowdedness in the center of Milan is proxied by aggregated mobile phone traffic data. We specify several desirable spatio-temporal properties related to city crowdedness such as a fault tolerant network or the reachability of hospitals. After verifying these properties on draws from the posterior predictive distributions, we compare several spatio-temporal Bayesian models based on their overall and property-based predictive performance.
    Keywords Statistics - Computation ; Computer Science - Logic in Computer Science
    Subject code 310
    Publishing date 2021-10-04
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  7. Book ; Online: Monitoring Mobile and Spatially Distributed Cyber-Physical Systems

    Bartocci, Ezio / Bortolussi, Luca / Loreti, Michele / Nenzi, Laura

    2019  

    Abstract: Cyber-Physical Systems~(CPS) consist of collaborative, networked and tightly intertwined computational (logical) and physical components, each operating at different spatial and temporal scales. Hence, the spatial and temporal requirements play an ... ...

    Abstract Cyber-Physical Systems~(CPS) consist of collaborative, networked and tightly intertwined computational (logical) and physical components, each operating at different spatial and temporal scales. Hence, the spatial and temporal requirements play an essential role for their correct and safe execution. Furthermore, the local interactions among the system components result in global spatio-temporal emergent behaviors often impossible to predict at the design time. In this work, we pursue a complementary approach by introducing STREL a novel spatio-temporal logic that enables the specification of spatio-temporal requirements and their monitoring over the execution of mobile and spatially distributed CPS. Our logic extends the Signal Temporal Logic with two novel spatial operators reach and escape from which is possible to derive other spatial modalities such as everywhere, somewhere and surround. These operators enable a monitoring procedure where the satisfaction of the property at each location depends only on the satisfaction of its neighbours, opening the way to future distributed online monitoring algorithms. We propose both a qualitative and quantitative semantics based on constraint semirings, an algebraic structure suitable for constraint satisfaction and optimisation. We prove that, for a subclass of models, all the spatial properties expressed with reach and escape, using euclidean distance, satisfy all the model transformations using rotation, reflection and translation. Finally, we provide an offline monitoring algorithm for STREL and, to demonstrate the feasibility of our approach, we show its application using the monitoring of a simulated mobile ad-hoc sensor network as running example.
    Keywords Computer Science - Logic in Computer Science
    Subject code 005
    Publishing date 2019-04-15
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: Context, Composition, Automation, and Communication -- The C2AC Roadmap for Modeling and Simulation

    Uhrmacher, Adelinde / Frazier, Peter / Hähnle, Reiner / Klügl, Franziska / Lorig, Fabian / Ludäscher, Bertram / Nenzi, Laura / Ruiz-Martin, Cristina / Rumpe, Bernhard / Szabo, Claudia / Wainer, Gabriel A. / Wilsdorf, Pia

    2023  

    Abstract: Simulation has become, in many application areas, a sine-qua-non. Most recently, COVID-19 has underlined the importance of simulation studies but also limitations in current practices and methods. We identify four goals of methodological work for ... ...

    Abstract Simulation has become, in many application areas, a sine-qua-non. Most recently, COVID-19 has underlined the importance of simulation studies but also limitations in current practices and methods. We identify four goals of methodological work for addressing these limitations. The first is to provide better support for capturing, representing, and evaluating the context of simulation studies, including research questions, assumptions, requirements, and activities that contributed to a simulation study and the generated artifacts, and how this contribution took place. In addition, the composition of simulation models and other products of simulation studies needs to be supported beyond syntactical coherence, including aspects of semantics and purpose, enabling their effective reuse. A higher degree of automating simulation studies will contribute to more systematic, standardized, qualitative simulation studies and their efficiency. Finally, it is essential to invest increased effort into effectively communicating results and the involved processes of simulation studies to enable their use in research and for decision-making. These goals are not pursued independently of each other, but they will benefit from and sometimes even rely on advances in each subfield. In the present paper, we explore the basis and interdependencies evident in current research and practice and delineate future research directions based on these considerations.
    Keywords Computer Science - Computational Engineering ; Finance ; and Science ; I.6
    Subject code 690
    Publishing date 2023-10-09
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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