Sophisticated imitation in cyclic games

Individuals belonging to two large populations are repeatedly randomly matched to play a cyclic game such as Matching Pennies. Between matching rounds, individuals sometimes change their strategy after observing a finite sample of other outcomes within their population. Individuals from the same population follow the same behavioral rule. In the resulting discrete time dynamics the unique Nash equilibrium is unstable. However, for sample sizes greater than one, we present an imitation rule where long run play cycles closely around the equilibrium.     

Stochastic imitation in finite games

In this paper we model an evolutionary process with perpetual random shocks, where individuals sample population-specific strategy-payoff pairs and imitate the most successful behavior. For finite n-player games we prove that in the limit, as the perturbations tend to zero, only strategy-tuples in minimal sets closed under single better replies will be played with positive probability. If the strategy-tuples in one such minimal set have strictly higher payoffs than all outside strategy-tuples, then the strategy-tuples in this set will be played with probability one in the limit, provided the minimal set is a product set and the sample is sufficiently large.     

Adaptation and complexity in repeated games

The paper presents a learning model for two-player infinitely repeated games. In an inference step players construct minimally complex inferences of strategies based on observed play, and in an adaptation step players choose minimally complex best responses to an inference. When players randomly select an inference from a probability distribution with full support the set of steady states is a subset of the set of Nash equilibria in which only stage game Nash equilibria are played. When players make ‘cautious’ inferences the set of steady states is the subset of self-confirming equilibria with Nash outcome paths. When players use different inference rules, the set of steady states can lie between the previous two cases.     

Strategic complexity in repeated extensive games

This paper studies a machine (finite automaton) playing a two-player repeated game of a simple extensive-form game with perfect information. We introduce a new complexity measure called multiple complexity which incorporates a strategyʼs responsiveness to information in the stage game as well as the number of states of the machine. We completely characterize the Nash equilibrium of the machine game. In the sequential-move prisonerʼs dilemma, cooperation can be sustained as an equilibrium.     

On the complexity of repeated principal agent games

Summary We examine an infinitely repeated principal agent game without discounting (Radner [1985]), in which the agent may engage in multiple projects. We focus on linear strategies that summarize each history into a linear function of public outcomes, and select an action according to a single threshold rule. We claim that linear strategies significantly simplify the computation needed to make strategic decisions following each history. Despite the simplicity of linear strategies, we can virtually recover the folk theorem. For any individually rational payoff vector in the interior of the set of feasible expected payoff vectors, there exists a pair of linear strategies that form a Nash equilibrium supporting the target payoff. The equilibrium strategies and the equilibrium payoff vectors form a globally stable solution (Smale [1980]).I would like to thank Andrew Atkeson and the anonymous referee for helpful comments. John Curran and Hao Li provided excellent research assistance. Financial support from the National Science Foundation, the Alfred P. Sloan Foundation and the Division of Social Sciences at the University of Chicago is gratefully acknowledged.     

On the complexity of repeated principal agent games?

Summary. We examine an infinitely repeated principal agent game without discounting (Radner [1985] ), in which the agent may engage in multiple projects. We focus on “linear” strategies that summarize each history into a linear function of public outcomes, and select an action according to a single threshold rule. We claim that linear strategies significantly simplify the computation needed to make strategic decisions following each history. Despite the simplicity of linear strategies, we can virtually recover the folk theorem. For any individually rational payoff vector in the interior of the set of feasible expected payoff vectors, there exists a pair of linear strategies that form a Nash equilibrium supporting the target payoff. The equilibrium strategies and the equilibrium payoff vectors form a globally stable solution (Smale [1980] ).     

Monotone imitation

We analyze the social learning process of a group of individuals who have limited information about the payoff distributions of each action. We say that a behavioral rule is first-order monotone (FOM) if the number of individuals who play actions with first-order stochastic dominant payoff distributions is expected to increase in any environment. We provide a characterization of FOM rules. Both Imitate if Better and Schlag’s (J Econ Theory 78:130–156, 1998) Proportional Imitation rule are FOM. No FOM rule is dominant in the sense of having the best performance in every environment.     

Cooperation through imitation

This paper characterizes long-run outcomes for broad classes of symmetric games, when players select actions on the basis of average historical performance. Received wisdom suggests that when agent's interests are partially opposed, behavior is excessively competitive: “keeping up with the Jones' ” lowers everyones' welfare. Here, we study the long-run consequences of imitative behavior when agents have sufficiently long memories and evaluate past actions in terms of (weighted) average payoff. Imitation robustly leads to cooperative outcomes (with highest symmetric payoffs) in the long run. Furthermore, lengthening memory reinforces this effect. This provides a rationale, for example, for collusive cartel-like behavior without collusive intent.     

Learning from private information in noisy repeated games

We study the perfect type-contingently public ex-post equilibrium (PTXE) of repeated games where players observe imperfect public signals of the actions played, and both the payoff functions and the map from actions to signal distributions depend on an unknown state. The PTXE payoffs when players are patient are determined by the solutions to a family of linear programming problems. Using this characterization, we develop conditions under which play can be as if the players have learned the state. We provide a sufficient condition for the folk theorem, and a characterization of the PTXE payoffs in games with a known monitoring structure.     

Patents,imitation and welfare

We consider the effects of product and process patents on profits and welfare. In a duopoly model, we show that if the cost of imitation is not very large, prisoner's dilemma occurs under process patent, thus creating lower profit of each firm under process patent than under product patent. Welfare is higher under process (product) patent for very small (not very small) cost of imitation. Although the possibility of cross-licensing never makes lower welfare under process patent for all costs of imitation, welfare is never lower under product patent under infinitely repeated game.     

Testing subgame perfection apart from fairness in ultimatum games

We present an experiment designed to separate the two commonplace explanations for behavior in ultimatum games—subjects’ concern for fairness versus the failure of subgame perfection as an equilibrium refinement. We employ a tournament structure of the bargaining interaction to eliminate the potential for fairness to influence behavior. Comparing the results of the tournament game with two control treatments affords us a clean test of subgame perfection as well as a measure fairness-induced play. We find after 10 iterations of play that about half of all non-subgame-perfect demands are due to fairness, and the rest to imperfect learning. However, as suggested by models of learning, we also confirm that the ultimatum game presents an especially difficult environment for learning subgame perfection. Electronic Supplementary Material Supplementary material is available in the online version of this article at . JEL Classification C91, D64, J52     

Random-player games

This paper introduces general games with incomplete information in which the number, as well as the types or identities, of the participating players are determined by chance and might not be known to the players when they make their choices of actions. In these games, the selection of the number and types of players is modeled as a finite point process on a suitable type space. Definitions of pure-strategy, mixed-strategy, and correlated equilibria in random-player games are given, extending the corresponding ones for finite games, Bayesian games, and games with population uncertainty, which may all be considered as special cases of random-player games.     

Monotone imitation dynamics in large populations

We analyze a class of imitation dynamics with mutations for games with any finite number of actions, and give conditions for the selection of a unique equilibrium as the mutation rate becomes small and the population becomes large. Our results cover the multiple-action extensions of the aspiration-and-imitation process of Binmore and Samuelson [Muddling through: noisy equilibrium selection, J. Econ. Theory 74 (1997) 235–265] and the related processes proposed by Benaı¨m and Weibull [Deterministic approximation of stochastic evolution in games, Econometrica 71 (2003) 873–903] and Traulsen et al. [Coevolutionary dynamics: from finite to infinite populations, Phys. Rev. Lett. 95 (2005) 238701], as well as the frequency-dependent Moran process studied by Fudenberg et al. [Evolutionary game dynamics in finite populations with strong selection and weak mutation, Theoretical Population Biol. 70 (2006) 352–363]. We illustrate our results by considering the effect of the number of periods of repetition on the selected equilibrium in repeated play of the prisoner's dilemma when players are restricted to a small set of simple strategies.     

Cooperation,imitation and partial rematching

We study a setting in which imitative players are matched into pairs to play a Prisonerʼs Dilemma game. A well-known result in such setting is that under random matching cooperation vanishes for any interior initial condition. The novelty of this paper is that we consider partial rematching: players that belong to a pair in which both parties cooperate repeat partner next period, while all other players are randomly matched into pairs. Under certain conditions, this rematching mechanism makes cooperation the unique outcome in the long run. Furthermore, we show that if imitation happens infrequently enough then cooperative behavior is always present in the population.     

The evolution of cooperation through imitation

We study evolutionarily stable outcomes for a class of games that admit cooperation and conflict as possible Nash equilibria. We make use of two ideas: existing strategies are more likely to be imitated than new strategies are to be introduced; players are able to identify opponents' behavior prior to interaction. The long-run evolutionary limit is efficient for the case of perfect recognition of opponents' behavior. For the case of imperfect recognition, efficiency is not achieved and long-run outcomes are more efficient the more accurate is the information. Strategies that emerge in the long run are those where players reward opponents who are likely to play the same way, and punish opponents who are likely to play differently.     

Punishment strategies in repeated games: Evidence from experimental markets

An experiment is designed to provide a snapshot of the strategies used by players in a repeated price competition game with a random continuation rule. One hundred pairs of subjects played the game over the Internet, with subjects having a few days to make their decisions in each round. Occasionally subjects are asked to enter one-period-ahead pricing strategies instead of prices. According to the elicited strategies, between 90% and 95% of subjects punish less harshly (in their initial response to a deviation) than implied by the grim trigger strategy, and do so in a way that depends on the size of the other subjectʼs deviation. Future earnings are highest for subjects adopting the tit-for-tat strategy, even after controlling for a subjectʼs past earnings. Punishment strategies are generally softer and more graduated than implied by a grim trigger strategy, and do better as a result.     

Separating the Hawks from the Doves: Evidence from continuous time laboratory games

Human players in our laboratory experiment received flow payoffs over 120 seconds each period from a standard Hawk–Dove bimatrix game played in continuous time. Play converged closely to the symmetric mixed Nash equilibrium under a one-population matching protocol. When the same players were matched in a two-population protocol with the same bimatrix, they showed clear movement towards an asymmetric (and very inequitable) pure Nash equilibrium of the game. These findings support distinctive predictions of evolutionary game theory.     

Austrian theories of entrepreneurship: Insights from complexity theory

This paper examines various Austrian theories of entrepreneurship through the lens of complexity theory, more specifically via the concept of a dancing fitness landscape. Problems in many fields (including economics) can be characterized as attempting to find the highest peak on a fitness landscape (which corresponds to an efficient or optimal resource allocation). A rugged fitness landscape is one characterized by many peaks and troughs, while a dancing fitness landscape is one where the peaks and troughs change over time due either to exogenous or endogenous activity. I argue that several key disagreements among Austrian economists can be better understood through the metaphor of a fitness landscape. The implications of this insight for various branches of Austrian economics are also considered. This study is timely as radical Austrian views are starting to percolate into business schools leading to increased debate among management scholars about the precise nature of the entrepreneurial process (Chiles et al. 2007; Sarasvathy and Dew 2008; Alvarez et al. 2010).     

Catch-up and fall-back through innovation and imitation

Will fast growing emerging economies sustain rapid growth rates until they “catch-up” to the technology frontier? Are there incentives for some developed countries to free-ride off of innovators and optimally “fall-back” relative to the frontier? This paper models agents growing as a result of investments in innovation and imitation. Imitation facilitates technology diffusion, with the productivity of imitation modeled by a catch-up function that increases with distance to the frontier. The resulting equilibrium is an endogenous segmentation between innovators and imitators, where imitating agents optimally choose to “catch-up” or “fall-back” to a productivity ratio below the frontier.