Szczegóły publikacji

Opis bibliograficzny

Scalable signal-based simulation of autonomous beings in complex environments / Mateusz PACIOREK, Agata Bogacz, Wojciech TUREK // W: Computational Science - ICCS 2020 : 20th International Conference : Amsterdam, The Netherlands, June 3–5, 2020 : proceedings, Pt. 3 / eds. Valeria V. Krzhizhanovskaya, [et al.]. — Cham : Springer Nature Switzerland, cop. 2020. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12139. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-030-50419-9; e-ISBN:  978-3-030-50420-5. — S. 144–157. — Bibliogr. s. 156–157, Abstr. — Publikacja dostępna online od: 2020-06-15

Autorzy (3)

Słowa kluczowe

scalabilityhigh performance computingagent based simulationautonomous beings simulation

Dane bibliometryczne

ID BaDAP129163
Data dodania do BaDAP2020-06-26
Tekst źródłowyURL
DOI10.1007/978-3-030-50420-5_11
Rok publikacji2020
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
WydawcaSpringer
KonferencjaInternational Conference on Computational Science 2020
Czasopisma/serieLecture Notes in Computer Science, Theoretical Computer Science and General Issues

Abstract

Simulation of groups of autonomous beings poses a great computational challenge in terms of required time and resources. The need to simulate large environments, numerous populations of beings, and to increase the detail of models causes the need for parallelization of computations. The signal-based simulation algorithm, presented in our previous research, prove the possibility of linear scalability of such computations up to thousands of computing cores. In this paper further extensions of the signal-based models are investigated and new method for defining complex environments is presented. It allows efficient and scalable simulation of structures which cannot be defined using two dimensions, like multi-story buildings, anthills or bee hives. The solution is applied for defining a building evacuation model, which is validated using empirical data from a real-life evacuation drill.

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