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Games
Special Issues
Social Learning and Cultural Evolution
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Social Learning and Cultural Evolution

A special issue of Games (ISSN 2073-4336). This special issue belongs to the section "Learning and Evolution in Games".

Deadline for manuscript submissions: closed (10 March 2022) | Viewed by 11800

Special Issue Editor

Prof. Karl H. Schlag

E-Mail Website
Guest Editor
Department of Economics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Wien, Austria
Interests: choice without priors, applied to learning and pricing; imitation and exact nonparametric statistics; game theory; industrial organization; microeconomics; economic theory and statistics; evolution

Special Issue Information

Dear Colleagues,

This is a call to all those working in Anthropology, Biology, Economics, Machine Learning, Mathematics, Psychology, Sociology and related fields to come together and share their insights in this very exciting field. Alone, we are weak; together, we are strong. We communicate and learn from one another. What we do influences what others do through social learning. Together, we form a society, developing a culture that has its own dynamics via cultural evolution. How does the individual entity influence the large and vice versa? What rules do we use and why? How does individual behavior influence the mass, and create and stabilize norms? In this special issue, we invite papers using different methods, from theory to simulations to data analyses, from a focus on individual behavior to a focus on learning as a population or society, as animals, humans or machines, towards contributions to research on social learning and cultural evolution. I am eagerly awaiting your contributions.

Karl H. Schlag
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Games is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • imitation
  • social learning
  • evolution
  • dynamics
  • norms
  • stability
  • equilibria

Published Papers (4 papers)

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Research

14 pages, 277 KiB  
Article
Social Learning between Groups: Imitation and the Role of Experience
by Karl H. Schlag
Games 2022, 13(5), 60; https://0-doi-org.brum.beds.ac.uk/10.3390/g13050060 - 06 Sep 2022
Viewed by 1366
Abstract
Social learning often occurs between groups with different levels of experience. Yet little is known about the ideal behavioral rules in such contexts. Existing insights only apply when individuals learn from each other in the same group. In this paper, we close this [...] Read more.
Social learning often occurs between groups with different levels of experience. Yet little is known about the ideal behavioral rules in such contexts. Existing insights only apply when individuals learn from each other in the same group. In this paper, we close this gap and consider two groups, novices and experienced. Experienced should not learn from novices. For novices learning from experienced, a particular form of probabilistic imitation is selected. Novices should imitate any experienced who is more successful, and sometimes but not always imitate an experienced who is less successful. Full article
(This article belongs to the Special Issue Social Learning and Cultural Evolution)
19 pages, 1052 KiB  
Article
The Evolution of Ambiguity in Sender—Receiver Signaling Games
by Roland Mühlenbernd, Sławomir Wacewicz and Przemysław Żywiczyński
Games 2022, 13(2), 20; https://0-doi-org.brum.beds.ac.uk/10.3390/g13020020 - 22 Feb 2022
Cited by 1 | Viewed by 3138
Abstract
We study an extended version of a sender–receiver signaling game—a context-signaling (CS) game that involves external contextual cues that provide information about a sender’s private information state. A formal evolutionary analysis of the investigated CS game shows that ambiguous signaling strategies can achieve [...] Read more.
We study an extended version of a sender–receiver signaling game—a context-signaling (CS) game that involves external contextual cues that provide information about a sender’s private information state. A formal evolutionary analysis of the investigated CS game shows that ambiguous signaling strategies can achieve perfect information transfer and are evolutionarily stable. Moreover, a computational analysis of the CS game shows that such perfect ambiguous systems have the same emergence probability as non-ambiguous perfect signaling systems in multi-agent simulations under standard evolutionary dynamics. We contrast these results with an experimental study where pairs of participants play the CS game for multiple rounds with each other in the lab to develop a communication system. This comparison shows that unlike virtual agents, human agents clearly prefer perfect signaling systems over perfect ambiguous systems. Full article
(This article belongs to the Special Issue Social Learning and Cultural Evolution)
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15 pages, 285 KiB  
Article
Evolution of Social Learning with Payoff and Content Bias
by Charles Perreault and Robert Boyd
Games 2022, 13(1), 7; https://0-doi-org.brum.beds.ac.uk/10.3390/g13010007 - 28 Dec 2021
Cited by 1 | Viewed by 2242
Abstract
There has been much theoretical work aimed at understanding the evolution of social learning; and in most of it, individual and social learning are treated as distinct processes. A number of authors have argued that this approach is faulty because the same psychological [...] Read more.
There has been much theoretical work aimed at understanding the evolution of social learning; and in most of it, individual and social learning are treated as distinct processes. A number of authors have argued that this approach is faulty because the same psychological mechanisms underpin social and individual learning. In previous work, we analyzed a simple model in which both individual and social learning are the result of a single learning process. Here, we extend this approach by showing how payoff and content biases evolve. We show that payoff bias leads to higher average fitness when environments are noisy and change rapidly. Content bias always evolves when the expected fitness benefits of alternative traits differ. Full article
(This article belongs to the Special Issue Social Learning and Cultural Evolution)
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26 pages, 4416 KiB  
Article
Social Learning Strategies and Cooperative Behaviour: Evidence of Payoff Bias, but Not Prestige or Conformity, in a Social Dilemma Game
by Robin Watson, Thomas J. H. Morgan, Rachel L. Kendal, Julie Van de Vyver and Jeremy Kendal
Games 2021, 12(4), 89; https://0-doi-org.brum.beds.ac.uk/10.3390/g12040089 - 23 Nov 2021
Cited by 1 | Viewed by 3851
Abstract
Human cooperation, occurring without reciprocation and between unrelated individuals in large populations, represents an evolutionary puzzle. One potential explanation is that cooperative behaviour may be transmitted between individuals via social learning. Using an online social dilemma experiment, we find evidence that participants’ contributions [...] Read more.
Human cooperation, occurring without reciprocation and between unrelated individuals in large populations, represents an evolutionary puzzle. One potential explanation is that cooperative behaviour may be transmitted between individuals via social learning. Using an online social dilemma experiment, we find evidence that participants’ contributions were more consistent with payoff-biased transmission than prestige-biased transmission or conformity. We also found some evidence for lower cooperation (i) when exposed to social information about peer cooperation levels than without such information, and (ii) in the prisoners’ dilemma game compared to the snowdrift game. A simulation model established that the observed cooperation was more likely to be caused by participants’ general propensity to cooperate than by the effect of social learning strategies employed within the experiment, but that this cooperative propensity could be reduced through selection. Overall, our results support previous experimental evidence indicating the role of payoff-biased transmission in explaining cooperative behaviour, but we find that this effect was small and was overwhelmed by participants’ general propensity for cooperation. Full article
(This article belongs to the Special Issue Social Learning and Cultural Evolution)
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