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2016 | OriginalPaper | Buchkapitel

4. Norms, Coordination, and Order

verfasst von : Shinji Teraji

Erschienen in: Evolving Norms

Verlag: Palgrave Macmillan US

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Abstract

The dissemination of knowledge is crucial in society. People live in a world of expectations about interactions with others’ actions. It is meaningful to discuss the social order only when all agents share the same perception of existing reality which includes others’ actions. People follow rules of behavior in society. Relying on rules is a device we have learned to use because our reason is insufficient to master the detail of complex reality. If rules are recognized as recurrent patterns of behavior, individuals act according to rules of conduct. The diffusion of shared behavioral patterns is necessary to obtain the social order. Shared rules facilitate the decision-making in complex situations by limiting the range of circumstances to which individuals have to pay attention.

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Fußnoten
1
In Maynard Smith (1982), a symmetrical game for two players is played repeatedly by the members of some large population. Pairs of players are formed by independent random draws from the population. For each member of the population, the expected utility of playing a given strategy depends upon the frequency with which the alternative strategies are being played in the population as a whole. It is assumed that, if one strategy yields a higher expected utility than another, the frequency with which the first strategy is played will tend to increase relative to that of the second.
 
2
In 1936, Hayek became president of the London Economic Club, and delivered an address entitled “Economics and Knowledge” on November 10 of that year (Caldwell, 2014).
 
3
Targets are moving rather than fixed. While people are gaining additional knowledge by learning from earlier mistakes, some of their knowledge is, at the same time, becoming obsolete.
 
4
Littlechild (1986) identifies three ideal typical modes, namely, what he calls the ‘neoclassical model,’ the ‘Austrian model,’ and the ‘radical subjectivist mode.’
 
5
Lachmann (1976) fully embraces the notion of radical subjectivity, and argues that every economic actor will have a unique plan or a set of expectations about the future value of resources.
 
6
There are two broad categories, namely, ‘computational complexity’ and ‘dynamic complexity’ (Rosser 2012). While the former involves considering a system from the standpoint of computability, the latter is defined as occurring in dynamical systems that do not converge to a point, a limit cycle, or a smooth expansion or contraction endogenously.
 
7
According to Caldwell (2014, p. 35), “he [F. A. Hayek] first encountered the idea while thinking about how a market system might work to co-ordinate human action in a world in which knowledge was both dispersed and subjectively held. But as he came to realize, such orders are ubiquitous: they can be found in nature, and they are integral for understanding the development of many of our most important social, cultural, and economic institutions.”
 
8
The prototype of what is called a cellular automaton is informally described as follows. Consider a finite chessboard in which each square can be one of different colors at each moment in time. Assume that we have a rule that specifies what the color of each square should be as a function of its four neighboring squares, that is, north, south, east, and west. Now let an initial pattern of colored squares be given. We then turn the system on and let the rule-of-state transition operate, examining the pattern that emerges as time passes. We watch the squares taking different colors at each time step in accordance, and look for the steady-state pattern (if any).
 
9
The concept of polycentricity was first envisaged in Polanyi (1951). Polycentricity emerges as a nonhierarchical, institutional, and cultural framework that makes possible the coexistence of multiple centers of decision-making with different objectives and values.
 
10
The most oft-quoted example of this principle is Craig Reynold’s ‘boids’ program. The simulated birds, or boids, on a computer screen can wheel in union and avoid obstacles as if conducting highly coordinated maneuvers. Each boid in the simulation obeys only three simple models: (1) maintain a minimum distance from other objects in the environment, (2) match velocities with other boids in the neighborhood, and (3) move toward the perceived center of mass of voids in the neighborhood.
 
11
See Sugden (1995) for a formal theory of focal points. In his model, there is a one-to-one relationship between labels and strategies, so that players are always able to distinguish between their strategies.
 
12
For example, Schelling asked New Haven residents to name the place and time they would meet someone in New York City on a given day, if they had failed to communicate more specifically on the subject. Although there is an extremely large number of possibilities, over half the individuals named the same place—Grand Central Station—and almost everyone named the same time—noon.
 
13
In coordination games, the simplest way to create a focal point is by communication and agreement. Many experimental studies demonstrate that the players can increase their level of coordination in such games by engaging in ‘cheap talk’ (Crawford 1998).
 
14
Since the publication of Lewis’s Convention, many game theorists have given various common knowledge assumptions underpinning any solution concept for games. See Brandenburger and Dekel (1988) and Brandenburger (1992).
 
15
This is about what kind of game the players wish to play with each other (Vanberg 2007). It is not the question of whether they can play a given game, but the question of how they, together with other players, may come to play a better game.
 
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Metadaten
Titel
Norms, Coordination, and Order
verfasst von
Shinji Teraji
Copyright-Jahr
2016
DOI
https://doi.org/10.1057/978-1-137-50247-6_4