Kevin Zollman

We study a low-rationality learning dynamics called probe and adjust. Our emphasis is on its properties in games of information transfer such as the Lewis signaling game or the Bala-Goyal network game. These games fall into the class of weakly better reply games, in which, starting from any action profile, there is a weakly better reply path to a strict Nash equilibrium. We prove that probe and adjust will be close to strict Nash equilibria in this class of games with arbitrarily high probability. In addition, we compare these asymptotic properties to short-run behavior

In recent years, many scholars have suggested that the Baldwin effect may play an important role in the evolution of language. However, the Baldwin effect is a multifaceted and controversial process and the assessment of its connection with language is difficult without a formal model. This paper provides a first step in this direction. We examine a game-theoretic model of the interaction between plasticity and evolution in the context of a simple language game. Additionally, we describe three distinct aspects of the Baldwin effect: the Simpson– Baldwin effect, the Baldwin expediting effect and the Baldwin optimizing effect. We find that a simple model of the evolution of language lends theoretical plausibility to the existence of the Simpson– Baldwin and the Baldwin optimizing effects in this arena, but not the Baldwin expediting effect

Recent research into the evolution of higher cognition has piqued an interest in the effect of natural selection on the ability of creatures to respond to their environment. It is believed that environmental variation is required for plasticity to evolve in cases where the ability to be plastic is costly. We investigate one form of environmental variation: frequency dependent selection. Using tools in game theory, we investigate a few models of plasticity and outline the cases where selection would be expected to maintain it. Ultimately we conclude that frequency dependent selection is likely insuffcient to maintain plasticity given reasonable assumptions about its costs. This result is very similar to one aspect of the well-discussed Baldwin effect, where plasticity is first selected for and then later selected against. We show how in these models one would expect plasticity to grow in the population and then be later reduced. Ultimately we conclude that if one is to account for the evolution of behavioral plasticity in this way, one must appeal to a very particular sort of external environmental variation

Increasingly, epistemologists are becoming interested in social structures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a community of scientists is, as a whole, more reliable when its members are less aware of their colleagues' experimental results. Second, there is a robust tradeoff between the reliability of a community and the speed with which it reaches a correct conclusion. ‡The author would like to thank Brian Skyrms, Kyle Stanford, Jeffrey Barrett, Bruce Glymour, and the participants in the Social Dynamics Seminar at University of California–Irvine for their helpful comments. Generous financial support was provided by the School of Social Science and Institute for Mathematical Behavioral Sciences at UCI. †To contact the author, please write to: Department of Philosophy, Baker Hall 135, Carnegie Mellon University, Pittsburgh, PA 15213-3890; e-mail: [email protected].

This paper approaches the problem of testimony from a new direction. Rather than focusing on the epistemic grounds for testimony, it considers the problem from the perspective of an individual who must choose whom to trust from a population of many would-be testifiers. A computer simulation is presented which illustrates that in many plausible situations, those who trust without attempting to judge the reliability of testifiers outperform those who attempt to seek out the more reliable members of the community. In so doing, it presents a novel defense for the credulist position that argues one should trust testimony without considering the underlying reliability of the testifier

In this paper we show that there are certain limits as to what applications of Maynard Smith’s concept of evolutionarily stable strategy can tell us about evolutionary processes. We shall argue that ESS is very similar in spirit to a particular branch of rational choice game theory, namely, the literature on refinements of Nash equilibrium. In the first place, ESS can also be viewed as a Nash equilibrium refinement. At a deeper level, ESS shares a common structure with other rational choice equilibrium refinements. An equilibrium is evaluated according to whether it persists under specific kinds of perturbations. In the case of ESS, these perturbations are mutations. However, from a dynamical point of view, focusing exclusively on perturbations of equilibria provides only a partial account of the system under consideration. We will show that this has important consequences when it comes to analyzing game-theoretic models of evolutionary processes. In particular, there are non-ESS states which are significant for evolutionary dynamics

Lewis signaling games illustrate how language might evolve from random behavior. The probability of evolving an optimal signaling language is, in part, a function of what learning strategy the agents use. Here we investigate three learning strategies, each of which allows agents to forget old experience. In each case, we find that forgetting increases the probability of evolving an optimal language. It does this by making it less likely that past partial success will continue to reinforce suboptimal practice. The learning strategies considered here show how forgetting past experience can promote learning in the context of games with suboptimal equilibria.

There is growing interest in understanding and eliciting division of labor within groups of scientists. This paper illustrates the need for this division of labor through a historical example, and a formal model is presented to better analyze situations of this type. Analysis of this model reveals that a division of labor can be maintained in two different ways: by limiting information or by endowing the scientists with extreme beliefs. If both features are present however, cognitive diversity is maintained indefinitely, and as a result agents fail to converge to the truth. Beyond the mechanisms for creating diversity suggested here, this shows that the real epistemic goal is not diversity but transient diversity.