What kind of game is everyday interaction?

Vollmer, Hendrik

doi:10.1177/1043463113492307

Cited by 11 publications

(6 citation statements)

References 68 publications

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“…GT models describe interactions between actors, who make decisions in order to reach a certain outcome. They can formalize the mechanisms and patterns actors perform in RS and thus be used to characterize these systems (Goeree & Holt, 1999; Helbing, 1994; Helbing & Balietti, 2011; Moss, 2001; Vollmer, 2013). Since several examples of such GT characterizations exist, choosing the right mechanism for the situation at hand is crucial, yet not always evident (Barreteau, Le Page, & Perez, 2007; Feld, 1997).…”

Section: Methodsmentioning

confidence: 99%

The Game Between Game Theory and Gaming Simulations: Design Choices

Roungas

Bekius

Meijer

2019

Simulation & Gaming

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Background. The abstraction of complex systems, which is required by default when modelling gaming simulations, is a convoluted and time-consuming process. For gaming simulations to be efficient and effective, the problem of the real system they imitate needs to be narrowed down and simplified as much as possible. Additionally, even after abstraction of the real system, multiple design decisions need to be made and these may differ depending on the gaming simulation. Aim. This article proposes a framework for formalizing, and consequently standardizing, expediting and simplifying, the modelling of gaming simulations. Method. The proposed framework applies game concepts pertaining to game theory in the abstraction of the real system and the game design decisions. Results. Application of the framework in three case studies reveals several advantages of incorporating game theory into game design, such as formally defining the game design elements and identifying the worst-case scenarios in the real-systems, to name but two. Conclusions. Given the framework’s advantages in general, and the game design recommendations it offers in particular, it is safe to conclude that, for the cases presented in this article, the framework make positive contributions towards the development of gaming simulations.

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Section: Methodsmentioning

confidence: 99%

The Game Between Game Theory and Gaming Simulations: Design Choices

Roungas

Bekius

Meijer

2019

Simulation & Gaming

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“…Several economists have since restated the case for a closer analysis of communication in social dilemmas. For example, Vollmer (2013) believes integrating microsociological investigations of everyday interaction with game theory offers analytical leverage in understanding coordination, while Sally (2002, 2005) refers specifically to the established notion of cheap talk:‘talk is not cheap, rather it is complicated, creative, implied, affective and effective, altering speaker and listener and any embedded game [. .…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…In sum, social dilemmas affect society at all levels, from international agreements to intimate relationships. We have argued that enriching traditional studies on cooperation requires extending the line of inquiry to verbal interaction (Goffman, 1961;Sally, 2002Sally, , 2005Vollmer, 2013). By exploring the registers available to individual actors and the alignments between actors, we hope to have highlighted the potential for fruitful interdisciplinary dialogue between sociology, economics and linguistics.…”

Section: Fundingmentioning

confidence: 99%

Verbal interaction in a social dilemma

Adams

Ludwiczak

Sharma

et al. 2022

Rationality and Society

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This study presents the first sociolinguistic examination of communication in a social dilemma. 90 participants (18 groups of 5) completed a modified public goods game with 2 rounds: an effort-based task and an unscripted online chat about the results. A linear regression shows that consensus-building language in the Round 1 chat affects cooperative behaviour in the Round 2 task. A qualitative analysis of 3 groups explores how participants use different recognisable styles of communication (registers) to strategically align with or disalign from one another (stancetaking). Each analysis is complemented with a quantitative visualisation of how (dis)alignment between participants unfolds in real-time. We found that successful groups employ registers associated with collective action, such as gameshow talk (‘ouch. £69 out of a possible £120’) to encourage, punish, and pledge allegiance to one another. Less successful groups use registers that risk evoking mistrust and reducing obligation, such as business talk (‘I approve’). We argue that a mixed methods approach to interaction and behaviour can reveal incremental shifts in consensus building that underpin quantitative outcomes.

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“…The two-player space includes many of the most famous economic games, such as the Prisoner's Dilemma and Chicken, as well as less recognized games, such as no-conflict and win–win games in which individuals' choices lead ‘non-strategically’ to outcomes that benefit all [ 41 ]. As mundane as these ‘non-game’ games are, their value is clear in the fact that most of our daily social exchanges, themselves the result of evolutionary processes, are similarly mundane [ 42 ]. Overall, the space parsimoniously captures an impressive variety of interdependence patterns found in human interactions [ 40 , 41 ], and successfully builds upon the legacy of the most classic and simple games to model institutional processes and behaviour.…”

Section: The Institutional Evolution Framework and A Model Within Itmentioning

confidence: 99%

A dynamic over games drives selfish agents to win–win outcomes

Frey

Atkisson

2020

Proc. R. Soc. B.

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Understanding human institutions, animal cultures and other social systems requires flexible formalisms that describe how their members change them from within. We introduce a framework for modelling how agents change the games they participate in. We contrast this between-game ‘institutional evolution’ with the more familiar within-game ‘behavioural evolution’. We model institutional change by following small numbers of persistent agents as they select and play a changing series of games. Starting from an initial game, a group of agents trace trajectories through game space by navigating to increasingly preferable games until they converge on ‘attractor’ games. Agents use their ‘institutional preferences' for game features (such as stability, fairness and efficiency) to choose between neighbouring games. We use this framework to pose a pressing question: what kinds of games does institutional evolution select for; what is in the attractors? After computing institutional change trajectories over the two-player space, we find that attractors have disproportionately fair outcomes, even though the agents who produce them are strictly self-interested and indifferent to fairness. This seems to occur because game fairness co-occurs with the self-serving features these agents do actually prefer. We thus present institutional evolution as a mechanism for encouraging the spontaneous emergence of cooperation among small groups of inherently selfish agents, without space, reputation, repetition, or other more familiar mechanisms. Game space trajectories provide a flexible, testable formalism for modelling the interdependencies of behavioural and institutional evolutionary processes, as well as a mechanism for the evolution of cooperation.

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What kind of game is everyday interaction?

Cited by 11 publications

References 68 publications

The Game Between Game Theory and Gaming Simulations: Design Choices

The Game Between Game Theory and Gaming Simulations: Design Choices

Verbal interaction in a social dilemma

A dynamic over games drives selfish agents to win–win outcomes

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