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The entropic basis of collective behaviour
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
2015 (English)In: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 12, no 106, 20150037Article in journal (Refereed) Published
Abstract [en]

We identify a unique viewpoint on the collective behaviour of intelligent agents. We first develop a highly general abstract model for the possible future lives these agents may encounter as a result of their decisions. In the context of these possibilities, we show that the causal entropic principle, whereby agents follow behavioural rules that maximize their entropy over all paths through the future, predicts many of the observed features of social interactions among both human and animal groups. Our results indicate that agents are often able to maximize their future path entropy by remaining cohesive as a group and that this cohesion leads to collectively intelligent outcomes that depend strongly on the distribution of the number of possible future paths. We derive social interaction rules that are consistent with maximum entropy group behaviour for both discrete and continuous decision spaces. Our analysis further predicts that social interactions are likely to be fundamentally based on Weber's law of response to proportional stimuli, supporting many studies that find a neurological basis for this stimulus-response mechanism and providing a novel basis for the common assumption of linearly additive 'social forces' in simulation studies of collective behaviour.

Place, publisher, year, edition, pages
2015. Vol. 12, no 106, 20150037
Keyword [en]
collective behaviour, maximum entropy, causal entropic principle, Galton-Watson process, Weber's law, entropic forces
National Category
Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-252970DOI: 10.1098/rsif.2015.0037ISI: 000353359900016OAI: oai:DiVA.org:uu-252970DiVA: diva2:812656
Available from: 2015-05-19 Created: 2015-05-18 Last updated: 2017-12-04Bibliographically approved

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