This paper provides an overview of our adaptation of Norton Long's concept of the “ecology of games” into a theoretical framework for analyzing institutional complexity. I discuss the basic concepts of the framework, discuss hypotheses related to fundamental questions in governance and policy, and outline some basic analytical approaches. The conclusion assesses the future prospects of the ecology of games framework, including future research needs for theoretical and empirical development.
Conformity is a type of social learning that has received considerable attention among social psychologists and human evolutionary ecologists, but existing empirical research does not identify conformity cleanly. Conformity is more than just a tendency to follow the majority; it involves an exaggerated tendency to follow the majority. The "exaggerated" part of this definition ensures that conformists do not show just any bias toward the majority, but a bias sufficiently strong to increase the size of the majority through time. This definition of conformity is compelling because it is the only form of frequency-dependent social influence that produces behaviorally homogeneous social groups. We conducted an experiment to see if players were conformists by separating individual and social learners. Players chose between two technologies repeatedly. Payoffs were random, but one technology had a higher expected payoff. Individual learners knew their realized payoffs after each choice, while social learners only knew the distribution of choices among individual learners. A subset of social learners behaved according to a classic model of conformity. The remaining social learners did not respond to frequency information. They were neither conformists nor nonconformists, but mavericks. Given this heterogeneity in learning strategies, a tendency to conform increased earnings dramatically.
The existence of social learning has been confirmed in diverse taxa, from apes to guppies. In order to advance our understanding of the consequences of social transmission and evolution of behaviour, however, we require statistical tools that can distinguish among diverse social learning strategies. In this paper, we advance two main ideas. First, social learning is diverse, in the sense that individuals can take advantage of different kinds of information and combine them in different ways. Examining learning strategies for different information conditions illuminates the more detailed design of social learning. We construct and analyse an evolutionary model of diverse social learning heuristics, in order to generate predictions and illustrate the impact of design differences on an organism's fitness. Second, in order to eventually escape the laboratory and apply social learning models to natural behaviour, we require statistical methods that do not depend upon tight experimental control. Therefore, we examine strategic social learning in an experimental setting in which the social information itself is endogenous to the experimental group, as it is in natural settings. We develop statistical models for distinguishing among different strategic uses of social information. The experimental data strongly suggest that most participants employ a hierarchical strategy that uses both average observed pay-offs of options as well as frequency information, the same model predicted by our evolutionary analysis to dominate a wide range of conditions.
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