Review of Agent-Based Evacuation Models in Python

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50020937" target="_blank" >RIV/62690094:18450/23:50020937 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-49008-8_40" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-49008-8_40</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-49008-8_40" target="_blank" >10.1007/978-3-031-49008-8_40</a>

Result language
angličtina
Original language name
Review of Agent-Based Evacuation Models in Python
Original language description
The aim of this paper is to explore agent-based evacuation models in Python by conducting a systematic literature search using the PRISMA methodology. The principles of evacuation models are briefly described. Python packages and libraries for agent-based modelling frameworks are explained. Two research questions are defined. The first question aims to find out what typical current agent-based evacuation models look like in sense of application domain and location, number of agents, time and space scale etc.). The second question focuses on the details of the use of the Python programming language and libraries in implementations of agent-based evacuation models. The results of the PRISMA review are presented. Overall, Python is a suitable language for the development of agent-based evacuation models, as evidenced by the number of programming libraries and tools, as well as the growing number of scientific publications in last six years. However, most of the currently published models suffer from many shortcomings. A main surprise is the lack of adherence to standards in describing the agent-based computational model, providing source code and sharing documentation of experiments.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2023, PT I
ISBN
978-3-031-49007-1
ISSN
2945-9133
e-ISSN
1611-3349
Number of pages
12
Pages from-to
511-522
Publisher name
Springer
Place of publication
Cham
Event location
Horta, Faial Island, Azores
Event date
Sep 5, 2023
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
001160573500040

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