Please use this identifier to cite or link to this item: doi:10.22028/D291-31069
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Title: Rejection-Based Simulation of Non-Markovian Agents on Complex Networks
Author(s): Großmann, Gerrit
Bortolussi, Luca
Wolf, Verena
Editor(s): Cherifi, Hocine
Gaito, Sabrina
Mendes, José Fernendo
Moro, Esteban
Rocha, Luis M.
Language: English
Title: Complex networks and their applications VIII : proceedings of the Eighth International Conference on Complex Networks and Their Applications
Startpage: 349
Endpage: 361
Publisher/Platform: Springer
Year of Publication: 2020
Place of publication: Cham
Title of the Conference: COMPLEX NETWORKS 2019
Place of the conference: Lisbon, Portugal
Publikation type: Conference Paper
Abstract: Stochastic models in which agents interact with their neighborhood according to a network topology are a powerful modeling framework to study the emergence of complex dynamic patterns in real-world systems. Stochastic simulations are often the preferred—sometimes the only feasible—way to investigate such systems. Previous research focused primarily on Markovian models where the random time until an interaction happens follows an exponential distribution. In this work, we study a general framework to model systems where each agent is in one of several states. Agents can change their state at random, influenced by their complete neighborhood, while the time to the next event can follow an arbitrary probability distribution. Classically, these simulations are hindered by high computational costs of updating the rates of interconnected agents and sampling the random residence times from arbitrary distributions. We propose a rejection-based, event-driven simulation algorithm to overcome these limitations. Our method over-approximates the instantaneous rates corresponding to inter-event times while rejection events counter-balance these over-approximations. We demonstrate the effectiveness of our approach on models of epidemic and information spreading.
DOI of the first publication: 10.1007/978-3-030-36687-2_29
URL of the first publication: https://link.springer.com/chapter/10.1007/978-3-030-36687-2_29
Link to this record: hdl:20.500.11880/29209
http://dx.doi.org/10.22028/D291-31069
ISBN: 978-3-030-36686-5
978-3-030-36687-2
Date of registration: 29-May-2020
Notes: Studies in computational intelligence ; volume 881
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Verena Wolf
Collections:UniBib – Die Universitätsbibliographie

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