Games

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Open AccessEditorial

Special Issue: Aspects of Game Theory and Institutional Economics

by Wolfram Elsner, Torsten Heinrich, Henning Schwardt and Claudius Gräbner

Games 2014, 5(3), 188-190; https://doi.org/10.3390/g5030188 - 4 Sep 2014

Cited by 1 | Viewed by 5909

Classical economists from Adam Smith to Thomas Malthus and to Karl Marx have considered the importance of direct interdependence and direct interactions for the economy. This was even more the case for original institutionalist thinkers such as Thorstein Veblen, John Commons, and Clarence Ayres. In their writings, direct interdependence, interactions (or transactions) among agents, with all beneficial and with all problematic consequences, took center stage in economic analysis. Why, for instance, do people adhere to a particular new fashion or trend? Because others do, after eminent people, wealthy people, the “leisure class” (T. Veblen), have made it a symbol for status. The new fashion, however, ceases to serve as such a symbol once too many people follow it. The constant effort put into following trends and adopting fashion turns out to be a social dilemma, driven by Veblenian instincts, such as invidious distinction in predatory societies, conspicuous consumption and emulation. [...] Full article

(This article belongs to the Special Issue Game Theory and Institutional Economics (incl. Evolutionary Games and American Evolutionary Institutionalism of the Veblen-ian Kind))

10260 KiB

Open AccessArticle

An Agent-Based Model of Institutional Life-Cycles

by Manuel Wäckerle, Bernhard Rengs and Wolfgang Radax

Games 2014, 5(3), 160-187; https://doi.org/10.3390/g5030160 - 18 Aug 2014

Cited by 11 | Viewed by 7860

Abstract

We use an agent-based model to investigate the interdependent dynamics between individual agency and emergent socioeconomic structure, leading to institutional change in a generic way. Our model simulates the emergence and exit of institutional units, understood as generic governed social structures. We show how endogenized trust and exogenously given leader authority influences institutional change, i.e., diversity in institutional life-cycles. It turns out that these governed institutions (de)structure in cyclical patterns dependent on the overall evolution of trust in the artificial society, while at the same time, influencing this evolution by supporting social learning. Simulation results indicate three scenarios of institutional life-cycles. Institutions may, (1) build up very fast and freeze the artificial society in a stable but fearful pattern (ordered system); (2) exist only for a short time, leading to a very trusty society (highly fluctuating system); and (3) structure in cyclical patterns over time and support social learning due to cumulative causation of societal trust (complex system). Full article

(This article belongs to the Special Issue Game Theory and Institutional Economics (incl. Evolutionary Games and American Evolutionary Institutionalism of the Veblen-ian Kind))

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820 KiB

Open AccessArticle

Learning in Networks—An Experimental Study Using Stationary Concepts

by Siegfried K. Berninghaus, Thomas Neumann and Bodo Vogt

Games 2014, 5(3), 140-159; https://doi.org/10.3390/g5030140 - 31 Jul 2014

Cited by 3 | Viewed by 6196

Abstract

Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 × 2 games used by Selten and Chmura [1]. Every participant played against four neighbors. As a distinct aspect our experimental design allows players to choose different strategies against each different neighbor. The games were played in two network structures: a lattice and a circle. We analyze our results with respect to three aspects. We first compare our results with the predictions of five different equilibrium concepts (Nash equilibrium, quantal response equilibrium, action-sampling equilibrium, payoff-sampling equilibrium, and impulse balance equilibrium) which represent the long-run equilibrium of a learning process. Secondly, we relate our results to four different learning models (impulse-matching learning, action-sampling learning, self-tuning EWA, and reinforcement learning) which are based on the (behavioral) round-by-round learning process. At last, we compare the data with the experimental results of Selten and Chmura [1]. One main result is that the majority of players choose the same strategy against each neighbor. As other results, we observe an order of predictive success for the equilibrium concepts that is different from the order shown by Selten and Chmura and an order of predictive success for the learning models that is only slightly different from the order shown in a recent paper by Chmura, Goerg and Selten [2]. Full article

(This article belongs to the Special Issue Social Networks and Network Formation 2013)

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Games, Volume 5, Issue 3 (September 2014) – 3 articles , Pages 140-190

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