Statistical physics of human cooperation

By Matjaz Perc, Jillian J. Jordan, David G. Rand, Zhen Wang, Stefano Boccaletti, Attila Szolnoki. arXiv.org, 2017

1,441 citations recorded by the source corpus.

Abstract Extensive cooperation among unrelated individuals is unique to humans, who often sacrifice personal benefits for the common good and work together to achieve what they are unable to execute alone. The evolutionary success of our species is indeed due, to a large degree, to our unparalleled other-regarding abilities. Yet, a comprehensive understanding of human cooperation remains a formidable challenge. Recent research in the social sciences indicates that it is important to focus on the collective behavior that emerges as the result of the interactions among individuals, groups, and even societies. Non-equilibrium statistical physics, in particular Monte Carlo methods and the theory of collective behavior of interacting particles near phase transition points, has proven to be very valuable for understanding counterintuitive evolutionary outcomes. By treating models of human cooperation as classical spin models, a physicist can draw on familiar settings from statistical physics. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among humans often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. The complexity of solutions therefore often surpasses that observed in physical systems. Here we review experimental and theoretical research that advances our understanding of human cooperation, focusing on spatial pattern formation, on the spatiotemporal dynamics of observed solutions, and on self-organization that may either promote or hinder socially favorable states.

Subfields: Genetics, Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/33b971746b312c1c6796f16a90432822cadd68d5

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Citations in the corpus

Network science of biological systems at different scales: A review. (2017, background): “[10] Perc M, Jordan JJ, Rand DG, Wang Z, Boccaletti S, Szolnoki A.”
What's the right thing to do? Increasing pro-sociality with simple moral nudges (2017, neutral): “…finding mechanisms to reduce free-riding and promote pro-social behaviour is of great importance for the well-being of our society (Karlan & List, 2007; Kraft-Todd et al, 2015; Martin & Randall, 2008; Ariely, Bracha & Meier, 2009; Capraro, 2013; Gneezy, Keenan & Gneezy, 2014; Perc et al, 2017).”
Second-order freeriding on antisocial punishment restores the effectiveness of prosocial punishment (2017, methodology): “By using the square lattice, we continue a long-standing tradition that begun with the work of Nowak and May [57], and which has since emerged as a default setup to reveal all evolutionary outcomes that are feasible within a particular version of the public goods game [56].”
Networks beyond pairwise interactions: structure and dynamics (2020, background): “[548] Matjaž Perc, Jillian J Jordan, David G Rand, Zhen Wang, Stefano Boccaletti, and Attila Szolnoki.”