University of Hertfordshire

By the same authors

Modelling the Social Buffering Hypothesis in an Artificial Life Environment

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Modelling the Social Buffering Hypothesis in an Artificial Life Environment. / Khan, Imran; Lewis, Matthew; Cañamero, Lola.

ALIFE 2020: The 2020 Conference on Artificial Life. ed. / Josh Bongard; Juniper Lovato; Laurent Hebert-Dufrésne; Radhakrishna Dasari; Lisa Soros. Vol. 32 The MIT Press, 2020. p. 393-401.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Khan, I, Lewis, M & Cañamero, L 2020, Modelling the Social Buffering Hypothesis in an Artificial Life Environment. in J Bongard, J Lovato, L Hebert-Dufrésne, R Dasari & L Soros (eds), ALIFE 2020: The 2020 Conference on Artificial Life. vol. 32, The MIT Press, pp. 393-401, 2020 Conference on Artificial Life, 13/07/20. https://doi.org/10.1162/isal_a_00302

APA

Khan, I., Lewis, M., & Cañamero, L. (2020). Modelling the Social Buffering Hypothesis in an Artificial Life Environment. In J. Bongard, J. Lovato, L. Hebert-Dufrésne, R. Dasari, & L. Soros (Eds.), ALIFE 2020: The 2020 Conference on Artificial Life (Vol. 32, pp. 393-401). The MIT Press. https://doi.org/10.1162/isal_a_00302

Vancouver

Khan I, Lewis M, Cañamero L. Modelling the Social Buffering Hypothesis in an Artificial Life Environment. In Bongard J, Lovato J, Hebert-Dufrésne L, Dasari R, Soros L, editors, ALIFE 2020: The 2020 Conference on Artificial Life. Vol. 32. The MIT Press. 2020. p. 393-401 https://doi.org/10.1162/isal_a_00302

Author

Khan, Imran ; Lewis, Matthew ; Cañamero, Lola. / Modelling the Social Buffering Hypothesis in an Artificial Life Environment. ALIFE 2020: The 2020 Conference on Artificial Life. editor / Josh Bongard ; Juniper Lovato ; Laurent Hebert-Dufrésne ; Radhakrishna Dasari ; Lisa Soros. Vol. 32 The MIT Press, 2020. pp. 393-401

Bibtex

@inproceedings{a50e3badcaf84d1da0651b57ab1e2010,
title = "Modelling the Social Buffering Hypothesis in an Artificial Life Environment",
abstract = "In social species, individuals who form social bonds have been found to live longer, healthier lives. One hypothesised reason for this effect is that social support, mediated by oxytocin, “buffers” responses to stress in a number of ways, and is considered an important process of adaptation that facilitates long-term wellbeing in changing, stressful conditions. Using an artificial life model, we have investigated the role of one hypothesised stress-reducing effect of social support on the survival and social interactions of agents in a small society. We have investigated this effect using different types of social bonds and bond partner combinations across environmentally-challenging conditions. Our results have found that stress reduction through social support benefits the survival of agents with social bonds, and that this effect often extends to the wider society. We have also found that this effect is significantly affected by environmental and social contexts. Our findings suggest that these “social buffering” effects may not be universal, but dependent upon the degree of environmental challenges, the quality of affective relationships and the wider social context.",
author = "Imran Khan and Matthew Lewis and Lola Ca{\~n}amero",
note = "{\textcopyright} 2020 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license: https://creativecommons.org/licenses/by/4.0/.; 2020 Conference on Artificial Life, ALIFE2020 ; Conference date: 13-07-2020 Through 18-07-2020",
year = "2020",
month = jul,
day = "14",
doi = "10.1162/isal_a_00302",
language = "English",
volume = "32",
pages = "393--401",
editor = "Josh Bongard and Juniper Lovato and Laurent Hebert-Dufr{\'e}sne and Radhakrishna Dasari and Lisa Soros",
booktitle = "ALIFE 2020",
publisher = "The MIT Press",
url = "http://www.alife.org/conference/alife-2020",

}

RIS

TY - GEN

T1 - Modelling the Social Buffering Hypothesis in an Artificial Life Environment

AU - Khan, Imran

AU - Lewis, Matthew

AU - Cañamero, Lola

N1 - © 2020 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license: https://creativecommons.org/licenses/by/4.0/.

PY - 2020/7/14

Y1 - 2020/7/14

N2 - In social species, individuals who form social bonds have been found to live longer, healthier lives. One hypothesised reason for this effect is that social support, mediated by oxytocin, “buffers” responses to stress in a number of ways, and is considered an important process of adaptation that facilitates long-term wellbeing in changing, stressful conditions. Using an artificial life model, we have investigated the role of one hypothesised stress-reducing effect of social support on the survival and social interactions of agents in a small society. We have investigated this effect using different types of social bonds and bond partner combinations across environmentally-challenging conditions. Our results have found that stress reduction through social support benefits the survival of agents with social bonds, and that this effect often extends to the wider society. We have also found that this effect is significantly affected by environmental and social contexts. Our findings suggest that these “social buffering” effects may not be universal, but dependent upon the degree of environmental challenges, the quality of affective relationships and the wider social context.

AB - In social species, individuals who form social bonds have been found to live longer, healthier lives. One hypothesised reason for this effect is that social support, mediated by oxytocin, “buffers” responses to stress in a number of ways, and is considered an important process of adaptation that facilitates long-term wellbeing in changing, stressful conditions. Using an artificial life model, we have investigated the role of one hypothesised stress-reducing effect of social support on the survival and social interactions of agents in a small society. We have investigated this effect using different types of social bonds and bond partner combinations across environmentally-challenging conditions. Our results have found that stress reduction through social support benefits the survival of agents with social bonds, and that this effect often extends to the wider society. We have also found that this effect is significantly affected by environmental and social contexts. Our findings suggest that these “social buffering” effects may not be universal, but dependent upon the degree of environmental challenges, the quality of affective relationships and the wider social context.

U2 - 10.1162/isal_a_00302

DO - 10.1162/isal_a_00302

M3 - Conference contribution

VL - 32

SP - 393

EP - 401

BT - ALIFE 2020

A2 - Bongard, Josh

A2 - Lovato, Juniper

A2 - Hebert-Dufrésne, Laurent

A2 - Dasari, Radhakrishna

A2 - Soros, Lisa

PB - The MIT Press

T2 - 2020 Conference on Artificial Life

Y2 - 13 July 2020 through 18 July 2020

ER -