Modelling the Social Buffering Hypothesis in an Artificial Life Environment

Imran Khan, Matthew Lewis, Lola Cañamero

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

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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.
Original languageEnglish
Title of host publicationALIFE 2020
Subtitle of host publicationThe 2020 Conference on Artificial Life
EditorsJosh Bongard, Juniper Lovato, Laurent Hebert-Dufrésne, Radhakrishna Dasari, Lisa Soros
PublisherMIT Press
Number of pages9
Publication statusPublished - 14 Jul 2020
Event2020 Conference on Artificial Life - Online Virtual Conference
Duration: 13 Jul 202018 Jul 2020


Conference2020 Conference on Artificial Life
Abbreviated titleALIFE2020
Internet address


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