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23rd International Workshop on Multi-Agent-Based Simulation, MABS 2022, collocated with the International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2022 ; 13743 LNAI:95-106, 2023.
Article in English | Scopus | ID: covidwho-2283591

ABSTRACT

Multi-agent based systems offer the possibility to examine the effects of policies down to specific target groups while also considering the effects on a population-level scale. To examine the impact of different schooling strategies, an agent-based model is used in the context of the COVID-19 pandemic using a German city as an example. The simulation experiments show that reducing the class size by rotating weekly between in-person classes and online schooling is effective at preventing infections while driving up the detection rate among children through testing during weeks of in-person attendance. While open schools lead to higher infection rates, a surprising result of this study is that school rotation is almost as effective at lowering infections among both the student population and the general population as closing schools. Due to the continued testing of attending students, the overall infections in the general population are even lower in a school rotation scenario, showcasing the potential for emergent behaviors in agent-based models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2.
Workshops on OptLearn-MAS, MABS, ABMUS, EMAS, and RAD-AI, held at the 21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022 ; 13441 LNAI:48-59, 2022.
Article in English | Scopus | ID: covidwho-2148616

ABSTRACT

Multi-agent based systems offer the possibility to examine the effects of policies down to specific target groups while also considering the effects on a population-level scale. To examine the impact of different schooling strategies, an agent-based model is used in the context of the COVID-19 pandemic using a German city as an example. The simulation experiments show that reducing the class size by rotating weekly between in-person classes and online schooling is effective at preventing infections while driving up the detection rate among children through testing during weeks of in-person attendance. While open schools lead to higher infection rates, a surprising result of this study is that school rotation is almost as effective at lowering infections among both the student population and the general population as closing schools. Due to the continued testing of attending students, the overall infections in the general population are even lower in a school rotation scenario, showcasing the potential for emergent behaviors in agent-based models. © 2022, Springer Nature Switzerland AG.

3.
20th International Conference on Practical Applications of Agents and Multi-Agent Systems , PAAMS 2022 ; 13616 LNAI:507-513, 2022.
Article in English | Scopus | ID: covidwho-2128474

ABSTRACT

During the COVID-19 pandemic, a rise of (agent-based) simulation models for predicting future developments and assessing intervention scenarios has been observed. At the same time, dashboarding has become a popular way to aggregate and visualise large quantities of data. The AScore Pandemic Management Cockpit brings together multiagent-based simulation (MABS) and analysis functionalities for crisis managers. It combines the presentation of data and forecasting on the effects of containment measures in a modular, reusable architecture that streamlines the process of use for these non-researcher users. In this paper, the most successful features and concepts for the simplification of simulation usage are presented: definition of scenarios, limitation of parameters, and integrated result visualisation, all bundled in a web-based service to offer a low-barrier entry to the usage of MABS in decision-making processes. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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