This paper focuses on defining and simulating behavioural outcomes of the bystander effect. These insights were modeled by temporal-causal networks. Typical patterns of bystander behaviour were translated into three requirements and seven simulated scenarios of the bystander effect. All scenarios were simulated to showcase the main bystander effect dynamics and its accordance with the literature. Unknown parameters of the effect were further estimated by a Simulated Annealing algorithm. In the end, the created model shows the potential to simulate the bystander effect in different and new scenarios. The created model adhered to the stated three requirements and shows potential to verify the model predictions independently and for new bystander situations.
|Title of host publication||Brain-Inspired Cognitive Architectures for Artificial Intelligence: BICA*AI 2020|
|Subtitle of host publication||Proceedings of the 11th Annual Meeting of the BICA Society|
|Editors||Alexei V. Samsonovich, Ricardo R. Gudwin, Alexandre da Simões|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||14|
|Publication status||Published - 2021|
|Event||11th Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence, BICA*AI 2020 - Natal, Brazil|
Duration: 10 Nov 2020 → 14 Nov 2020
|Name||Advances in Intelligent Systems and Computing|
|Conference||11th Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence, BICA*AI 2020|
|Period||10/11/20 → 14/11/20|
Bibliographical notePublisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Copyright 2020 Elsevier B.V., All rights reserved.
- Bystander effect
- Network modelling
- Simulated annealing