Carmine Spagnuolo

2025

1. KDD

   Hypergraph Motifs Representation Learning

   Antelmi, Alessia, Cordasco, Gennaro, De Vinco, Daniele, Di Pasquale, Valerio, Polato, Mirko, and Spagnuolo, Carmine

   2025

   Bib

   @inproceedings{KDD2025,
     author = {Antelmi, Alessia and Cordasco, Gennaro and De Vinco, Daniele and Di Pasquale, Valerio and Polato, Mirko and Spagnuolo, Carmine},
     title = {Hypergraph Motifs Representation Learning},
     year = {2025},
     journal = {31st SIGKDD Conference on Knowledge Discovery and Data Mining - Research Track (Accepted at August 2024 Deadline)},
     type = {Conference paper},
     bibtex_show = {true},
     selected = {true},
     abbr = {KDD},
     sjr = {<a href="https://portal.core.edu.au/conf-ranks/26/"><img border="0" src="https://img.shields.io/badge/Core'23-A*-blue.svg" alt="Core'23-A*"  /></a>}
   }

2024

1. ACCESS

   Are Claims Grounded in Data? An Empowering Linking Approach for Misalignment Identification in Online Data-driven Discussions

   Citro, Tiziano, Pellegrino, Maria Angela, and Spagnuolo, Carmine

   2024

   DOI Bib

   @article{10776984,
     author = {Citro, Tiziano and Pellegrino, Maria Angela and Spagnuolo, Carmine},
     journal = {IEEE Access},
     title = {Are Claims Grounded in Data? An Empowering Linking Approach for Misalignment Identification in Online Data-driven Discussions},
     year = {2024},
     volume = {},
     number = {},
     pages = {1-1},
     selected = {true},
     bibtex_show = {true},
     keywords = {Data visualization;Visualization;Hypertext systems;Switches;Layout;Data models;Bars;Visual databases;Soft sensors;Object oriented modeling;Data-driven discussions;Data visualization;Deixis;Linking;Misalignment;User study;Within-subjects design},
     doi = {10.1109/ACCESS.2024.3511039},
     abbr = {ACCESS},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=21100374601&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=21100374601" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }

2. JASSS

   Reliable and Efficient Agent-Based Modeling and Simulation

   Antelmi, Alessia, Caramante, Pasquale, Cordasco, Gennaro, D’Ambrosio, Giuseppe, De Vinco, Daniele, Foglia, Francesco, Postiglione, Luca, and Spagnuolo, Carmine

   2024

   DOI Abs Bib

   Agent-based models represent a primary methodology to untangle and study complex systems. Over the last decade, the need for more elaborate computing-demanding models gave rise to many frameworks and tools to run ABM simulations. Current state-of-the-art ABM tools either focus on ease of use, performance, or a trade-off between these two elements. Still, efficiency-oriented solutions (required for both large and small-scale simulations) are vulnerable to memory flaws which could invalidate the experiment results. This work aims to merge efficiency, reliability, and safeness under an innovative ABM software framework based on the Rust programming language. Our framework, krABMaga, is an open-source library that offers a high-level environment by exploiting metaprogramming and expandable visualization features. We equipped our library with a dynamic simulation monitoring system and model exploration and optimization capabilities over parallel, distributed, and cloud architectures. After having presented the overall architecture and functionalities of krABMaga, we discuss a performance comparison of our framework against the mostly adopted ABM software and the scalability potential of our simulation engine on a model calibration experiment running over an AWS EC2 virtual cluster machine. All code and examples models are available on GitHub.

   @article{antelmi2024,
     title = {Reliable and Efficient Agent-Based Modeling and Simulation},
     author = {Antelmi, Alessia and Caramante, Pasquale and Cordasco, Gennaro and D'Ambrosio, Giuseppe and De Vinco, Daniele and Foglia, Francesco and Postiglione, Luca and Spagnuolo, Carmine},
     journal = {Journal of Artificial Societies and Social Simulation},
     issn = {1460-7425},
     volume = {27},
     number = {2},
     pages = {4},
     year = {2024},
     bibtex_show = {true},
     url = {http://jasss.soc.surrey.ac.uk/27/2/4.html},
     doi = {10.18564/jasss.5300},
     selected = {true},
     abbr = {JASSS},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=23038&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=15591" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }

2023

1. CURS

   A Survey on Hypergraph Representation Learning

   Antelmi, Alessia, Cordasco, Gennaro, Polato, Mirko, Scarano, Vittorio, Spagnuolo, Carmine, and Yang, Dingqi

   ACM Computing Surveys 2023

   DOI Abs Bib

   Hypergraphs have attracted increasing attention in recent years thanks to their flexibility in naturally modeling a broad range of systems where high-order relationships exist among their interacting parts. This survey reviews the newly born hypergraph representation learning problem, whose goal is to learn a function to project objects - most commonly nodes - of an input hyper-network into a latent space such that both the structural and relational properties of the network can be encoded and preserved. We provide a thorough overview of existing literature and offer a new taxonomy of hypergraph embedding methods by identifying three main families of techniques, i.e., spectral, proximity-preserving, and (deep) neural networks. For each family, we describe its characteristics and our insights in a single yet flexible framework and then discuss the peculiarities of individual methods, as well as their pros and cons. We then review the main tasks, datasets, and settings in which hypergraph embeddings are typically used. We finally identify and discuss open challenges that would inspire further research in this field. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

   @article{Antelmi2024,
     author = {Antelmi, Alessia and Cordasco, Gennaro and Polato, Mirko and Scarano, Vittorio and Spagnuolo, Carmine and Yang, Dingqi},
     title = {A Survey on Hypergraph Representation Learning},
     year = {2023},
     journal = {ACM Computing Surveys},
     volume = {56},
     number = {1},
     doi = {10.1145/3605776},
     url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172393798&doi=10.1145%2f3605776&partnerID=40&md5=c9fa8ddc69d17c48c1e4b10d4d2703ce},
     author_keywords = {hypergraph attention; hypergraph convolution; hypergraph embedding; hypergraph neural networks; Hypergraph representation learning},
     keywords = {Convolution; Embeddings; Hyper graph; Hypergraph attention; Hypergraph convolution; Hypergraph embedding; Hypergraph neural network; Hypergraph representation learning; Hypergraph representations; Neural-networks; Embeddings},
     publisher = {Association for Computing Machinery},
     type = {Article},
     publication_stage = {Final},
     source = {Scopus},
     bibtex_show = {true},
     note = {All Open Access, Bronze Open Access},
     selected = {true},
     abbr = {CURS},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=23038&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=23038" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }

2022

1. ACCESS

   A Volunteer Computing Architecture for Computational Workflows on Decentralized Web

   Antelmi, Alessia, D’Ambrosio, Giuseppe, Petta, Andrea, Serra, Luigi, and Spagnuolo, Carmine

   IEEE Access 2022

   DOI Abs Bib

   The amount of accessible computational devices over the Internet offers an enormous but latent computational power. Nonetheless, the complexity of orchestrating and managing such devices requires dedicated architectures and tools and hinders the exploitation of this vast processing capacity. Over the last years, the paradigm of (Browser-based) Volunteer Computing emerged as a unique approach to harnessing such computational capabilities, leveraging the idea of voluntarily offering resources. This article proposes VFuse, a groundbreaking architecture to exploit the Browser-based Volunteer Computing paradigm via a ready-to-access volunteer network. VFuse offers a modern multi-language programming environment for developing scientific workflows using WebAssembly technology without requiring the user any local installation or configuration. We equipped our architecture with a secure and transparent rewarding mechanism based on blockchain technology (Ethereum) and distributed P2P file system (IPFS). Further, the use of Non-Fungible Tokens provides a unique, secure, and transparent methodology for recognizing the users’ participation in the network. We developed a prototype of the proposed architecture and four example applications implemented with our system. All code and examples are publicly available on GitHub. © 2013 IEEE.

   @article{Antelmi202298993,
     author = {Antelmi, Alessia and D'Ambrosio, Giuseppe and Petta, Andrea and Serra, Luigi and Spagnuolo, Carmine},
     title = {A Volunteer Computing Architecture for Computational Workflows on Decentralized Web},
     year = {2022},
     journal = {IEEE Access},
     volume = {10},
     pages = {98993 – 99010},
     doi = {10.1109/ACCESS.2022.3207167},
     url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139226212&doi=10.1109%2fACCESS.2022.3207167&partnerID=40&md5=8aa3ae4a0824a7feac90d241d217a2c2},
     author_keywords = {browser-based volunteer computing; decentralized web; distributed computing; P2P; parallel computing; Scientific computing; volunteer computing; Web 3.0; WebAssembly},
     keywords = {Cluster computing; Computer architecture; File organization; Natural sciences computing; Peer to peer networks; Software prototyping; Browser-based volunteer computing; Computing architecture; Decentralised; Decentralized web; P2P; Parallel com- puting; Volunteer computing; Web 3.0; Webassembly; Network architecture},
     publisher = {Institute of Electrical and Electronics Engineers Inc.},
     type = {Article},
     publication_stage = {Final},
     source = {Scopus},
     bibtex_show = {true},
     note = {All Open Access, Gold Open Access},
     selected = {true},
     abbr = {ACCESS},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=21100374601&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=21100374601" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }

2021

1. FGCS

   Easy and efficient agent-based simulations with the OpenABL language and compiler

   Cosenza, Biagio, Popov, Nikita, Juurlink, Ben, Richmond, Paul, Chimeh, Mozhgan Kabiri, Spagnuolo, Carmine, Cordasco, Gennaro, and Scarano, Vittorio

   Future Generation Computer Systems 2021

   DOI Abs Bib

   Agent-based simulations represent an effective scientific tool, with numerous applications from social sciences to biology, which aims to emulate or predict complex phenomena through a set of simple rules performed by multiple agents. To simulate a large number of agents with complex models, practitioners have developed high-performance parallel implementations, often specialized for particular scenarios and target hardware. It is, however, difficult to obtain portable simulations, which achieve high performance and at the same time are easy to write and to reproduce on different hardware. This article gives a complete presentation of OPENABL, a domain-specific language and a compiler for agent-based simulations that enable users to achieve high-performance parallel and distributed agent simulations with a simple and portable programming environment. OPENABL is comprised of (1) an easy-to-program language, which relies on domain abstractions and explicitly exposes agent parallelism, synchronization and locality, (2) a source-to-source compiler, and (3) a set of pluggable compiler backends, which generate target code for multi-core CPUs, GPUs, and cloud-based systems. We evaluate OPENABL on simulations from different fields. In particular, our analysis includes predator–prey and keratinocyte, two complex simulations with multiple step functions, heterogeneous agent types, and dynamic creation and removal of agents. The results show that OPENABL-generated codes are portable to different platforms, perform similarly to manual target-specific implementations, and require significantly fewer lines of codes. © 2020 Elsevier B.V.

   @article{Cosenza202161,
     author = {Cosenza, Biagio and Popov, Nikita and Juurlink, Ben and Richmond, Paul and Chimeh, Mozhgan Kabiri and Spagnuolo, Carmine and Cordasco, Gennaro and Scarano, Vittorio},
     title = {Easy and efficient agent-based simulations with the OpenABL language and compiler},
     year = {2021},
     journal = {Future Generation Computer Systems},
     volume = {116},
     pages = {61 – 75},
     doi = {10.1016/j.future.2020.10.014},
     url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094807912&doi=10.1016%2fj.future.2020.10.014&partnerID=40&md5=735a69df97f97ec7ec5a8fed0af442c2},
     author_keywords = {Agent-based simulation; Compilers; Domain specific language; GPU; Parallel and distributed computing},
     keywords = {Codes (symbols); Computer aided software engineering; Multi agent systems; Multicore programming; Problem oriented languages; Agent based simulation; Complex simulation; Distributed agents; Domain abstraction; Domain specific languages; Heterogeneous agents; Parallel implementations; Portable programming; Program compilers},
     publisher = {Elsevier B.V.},
     type = {Article},
     publication_stage = {Final},
     source = {Scopus},
     bibtex_show = {true},
     note = {All Open Access, Green Open Access},
     selected = {true},
     abbr = {FGCS},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=12264&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=12264" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }

2. ACCESS

   Modeling and Evaluating Epidemic Control Strategies with High-Order Temporal Networks

   Antelmi, Alessia, Cordasco, Gennaro, Scarano, Vittorio, and Spagnuolo, Carmine

   IEEE Access 2021

   DOI Abs Bib

   Non-Pharmaceutical Interventions (NPIs) are essential measures that reduce and control a severe outbreak or a pandemic, especially in the absence of drug treatments. However, estimating and evaluating their impact on society remains challenging, considering the numerous and closely tied aspects to examine. This article proposes a fine-grain modeling methodology for NPIs, based on high-order relationships between people and environments, mimicking direct and indirect contagion pathways over time. After assessing the ability of each intervention in controlling an epidemic propagation, we devise a multi-objective optimization framework, which, based on the epidemiological data, calculates the NPI combination that should be implemented to minimize the spread of an epidemic as well as the damage due to the intervention. Each intervention is thus evaluated through an agent-based simulation, considering not only the reduction in the fraction of infected but also to what extent its application damages the daily life of the population. We run experiments on three data sets, and the results illustrate how the application of NPIs should be tailored to the specific epidemic situation. They further highlight the critical importance of correctly implementing personal protective (e.g., using face masks) and sanitization measures to slow down a pathogen spreading, especially in crowded places. © 2013 IEEE.

   @article{Antelmi2021140938,
     author = {Antelmi, Alessia and Cordasco, Gennaro and Scarano, Vittorio and Spagnuolo, Carmine},
     title = {Modeling and Evaluating Epidemic Control Strategies with High-Order Temporal Networks},
     year = {2021},
     journal = {IEEE Access},
     volume = {9},
     pages = {140938 – 140964},
     doi = {10.1109/ACCESS.2021.3119459},
     url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117271030&doi=10.1109%2fACCESS.2021.3119459&partnerID=40&md5=232fb6a08035e13b637dafa7956546c8},
     author_keywords = {Agent-based modeling; complex networks; epidemic; high-order relationships; hypergraphs; non-pharmaceutical interventions},
     keywords = {Autonomous agents; Biological systems; Complex networks; Controlled drug delivery; Disease control; Multiobjective optimization; Agent-based model; Biological system modeling; Context models; High-order; High-order relationship; Higher-order; Hyper graph; Non-pharmaceutical interventions; Pandemic; Social networking (online); Computational methods},
     publisher = {Institute of Electrical and Electronics Engineers Inc.},
     type = {Article},
     publication_stage = {Final},
     source = {Scopus},
     bibtex_show = {true},
     note = {All Open Access, Gold Open Access},
     selected = {true},
     abbr = {ACCESS},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=21100374601&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=21100374601" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }

2020

1. AAMAS

   A design-methodology for epidemic dynamics via time-varying hypergraphs

   Antelmi, Alessia, Cordasco, Gennaro, Spagnuolo, Carmine, and Scarano, Vittorio

   In Proceedings of the International Joint INPROCEEDINGS on Autonomous Agents and Multiagent Systems, AAMAS 2020

   Abs Bib

   In epidemiology science, the importance to explore innovative modeling tools for acutely analyzing epidemic diffusion is turning into a big challenge considering the myriad of real-world aspects to capture. Typically, equation-based models, such as SIS and SIR, are used to study the propagation of diseases over a population. Improved approaches also include human-mobility patterns as network information to describe contacts among individuals. However, there still is the need to incorporate in these models information about different types of contagion, geographical information, humans habits, and environmental properties. In this paper, we propose a novel approach that takes into account: 1. direct and indirect epidemic contagion pathways to explore the dynamics of the epidemic, 2. the times of possible contagions, and 3. human-mobility patterns. We combine these three features exploiting time-varying hypergraphs, and we embed this model into a design-methodology for agent-based models (ABMs), able to improve the correctness in the epidemic estimations of classical contact-network approaches. We further describe a diffusion algorithm suitable for our design-methodology and adaptable to the peculiarities of any disease spreading policies and/or models. Finally, we tested our methodology by developing an ABM, realizing the SIS epidemic compartmental model, for simulating an epidemic propagation over a population of individuals. We experimented the model using real user-mobility data from the location-based social network Foursquare, and we demonstrated the high-impact of temporal direct and indirect contagion pathways. © 2020 International Foundation for Autonomous.

   @inproceedings{Antelmi202061,
     author = {Antelmi, Alessia and Cordasco, Gennaro and Spagnuolo, Carmine and Scarano, Vittorio},
     title = {A design-methodology for epidemic dynamics via time-varying hypergraphs},
     year = {2020},
     journal = {Proceedings of the International Joint INPROCEEDINGS on Autonomous Agents and Multiagent Systems, AAMAS},
     volume = {2020-May},
     pages = {61 – 69},
     url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096648502&partnerID=40&md5=e3c65524a0e801fcf4224635406e0bed},
     author_keywords = {Agent-based Model; Direct and indirect infection; Epidemiology; Location-based Social Network; Time-Varying Hypergraph},
     keywords = {Computational methods; Design; Epidemiology; Graph theory; Multi agent systems; Compartmental model; Diffusion algorithm; Environmental property; Epidemic propagation; Equation-based models; Geographical information; Location-based social networks; Network information; Autonomous agents},
     publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
     type = {INPROCEEDINGS paper},
     publication_stage = {Final},
     source = {Scopus},
     bibtex_show = {true},
     selected = {true},
     abbr = {AAMAS},
     sjr = {<a href="https://portal.core.edu.au/conf-ranks/922/"><img border="0" src="https://img.shields.io/badge/Core'23-A*-blue.svg" alt="Core'23-A*"  /></a>}
   }

2018

1. SIMPAT

   Distributed simulation optimization and parameter exploration framework for the cloud

   Carillo, Michele, Cordasco, Gennaro, Serrapica, Flavio, Scarano, Vittorio, Spagnuolo, Carmine, and Szufel, Przemysław

   Simulation Modelling Practice and Theory 2018

   DOI Abs Bib

   Simulation models are becoming an increasingly popular tool for the analysis and optimization of complex real systems in different fields. Finding an optimal system design requires performing a large sweep over the parameter space in an organized way. Hence, the model optimization process is extremely demanding from a computational point of view, as it requires careful, time-consuming, complex orchestration of coordinated executions. In this paper, we present the design of SOF (Simulation Optimization and exploration Framework in the cloud), a framework which exploits the computing power of a cloud computational environment in order to carry out effective and efficient simulation optimization strategies. SOF offers several attractive features. Firstly, SOF requires “zero configuration” as it does not require any additional software installed on the remote node; only standard Apache Hadoop and SSH access are sufficient. Secondly, SOF is transparent to the user, since the user is totally unaware that the system operates on a distributed environment. Finally, SOF is highly customizable and programmable, since it enables the running of different simulation optimization scenarios using diverse programming languages – provided that the hosting platform supports them – and different simulation toolkits, as developed by the modeler. The tool has been fully developed and is available on a public repository1 under the terms of the open source Apache License. It has been tested and validated on several private platforms, such as a dedicated cluster of workstations, as well as on public platforms, including the Hortonworks Data Platform and Amazon Web Services Elastic MapReduce solution. © 2017 Elsevier B.V.

   @article{Carillo2018108,
     author = {Carillo, Michele and Cordasco, Gennaro and Serrapica, Flavio and Scarano, Vittorio and Spagnuolo, Carmine and Szufel, Przemysław},
     title = {Distributed simulation optimization and parameter exploration framework for the cloud},
     year = {2018},
     journal = {Simulation Modelling Practice and Theory},
     volume = {83},
     pages = {108 – 123},
     doi = {10.1016/j.simpat.2017.12.005},
     url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039448974&doi=10.1016%2fj.simpat.2017.12.005&partnerID=40&md5=4c973bd636f16a60e4cae1198d244b2b},
     author_keywords = {Agent-based simulation; Cloud computing; Distributed computing; Model exploration; Parallel computing; Simulation optimization},
     keywords = {Cloud computing; Computer software; Coordination reactions; Distributed computer systems; HTTP; Modeling languages; Multiprocessing systems; Open source software; Parallel processing systems; Systems analysis; Web services; Agent based simulation; Cluster of workstations; Computational environments; Distributed environments; Distributed simulations; Efficient simulation; Parameter exploration; Simulation optimization; Computer simulation languages},
     publisher = {Elsevier B.V.},
     type = {Article},
     publication_stage = {Final},
     source = {Scopus},
     bibtex_show = {true},
     selected = {true},
     abbr = {SIMPAT},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=12189&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=12189" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }

2. SIMPAT

   Distributed MASON: A scalable distributed multi-agent simulation environment

   Cordasco, Gennaro, Scarano, Vittorio, and Spagnuolo, Carmine

   Simulation Modelling Practice and Theory 2018

   DOI Abs Bib

   Computational Social Science (CSS) involves interdisciplinary fields and exploits computational methods, such as social network analysis as well as computer simulation with the goal of better understanding social phenomena. Agent-Based Models (ABMs) represent an effective research tool for CSS and consist of a class of models, which, aim to emulate or predict complex phenomena through a set of simple rules (i.e., independent actions, interactions and adaptation), performed by multiple agents. The efficiency and scalability of ABMs systems are typically obtained distributing the overall computation on several machines, which interact with each other in order to simulate a specific model. Unfortunately, the design of a distributed simulation model is particularly challenging, especially for domain experts who sporadically are computer scientists and are not used to developing parallel code. D-MASON framework is a distributed version of the MASON library for designing and executing ABMs in a distributed environment ensuring scalability and easiness. D-MASON enable the developer to exploit the computing power of distributed environment in a transparent manner; the developer has to do simple incremental modifications to existing MASON models, without re-designing them. This paper presents several novel features and architectural improvements introduced in the D-MASON framework: an improved space partitioning strategy, a distributed 3D field, a distributed network field, a decentralized communication layer, a novel memory consistency mechanism and the integration to cloud environments. Full documentation, additional tutorials, and other material can be found at https://github.com/isislab-unisa/dmason where the framework can be downloaded. © 2018

   @article{Cordasco201815,
     author = {Cordasco, Gennaro and Scarano, Vittorio and Spagnuolo, Carmine},
     title = {Distributed MASON: A scalable distributed multi-agent simulation environment},
     year = {2018},
     journal = {Simulation Modelling Practice and Theory},
     volume = {89},
     pages = {15 – 34},
     doi = {10.1016/j.simpat.2018.09.002},
     url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053387248&doi=10.1016%2fj.simpat.2018.09.002&partnerID=40&md5=69e8f22545e4d5863d2f37d7ea10ac01},
     author_keywords = {Agent-based simulation; Cloud computing; Distributed computing; Parallel computing; Scalable computational science},
     keywords = {Autonomous agents; Cloud computing; Computational methods; Distributed computer systems; Parallel processing systems; Scalability; Agent based simulation; Architectural improvements; Computational science; Computational social science; Decentralized communications; Distributed simulation modeling; Interdisciplinary fields; Space-partitioning strategy; Multi agent systems},
     publisher = {Elsevier B.V.},
     type = {Article},
     publication_stage = {Final},
     source = {Scopus},
     bibtex_show = {true},
     selected = {true},
     abbr = {SIMPAT},
     sjr = {<a href="https://www.scimagojr.com/journalsearch.php?q=12189&amp;tip=sid&amp;exact=no" title="SCImago Journal &amp; Country Rank"><img border="0" src="https://www.scimagojr.com/journal_img.php?id=12189" alt="SCImago Journal &amp; Country Rank"  /></a>}
   }