Strategic Interaction in Humans and Other Animals

The history of game theory goes back to early 20th-century works by Emile Borel, Ernst Zermelo, and John von Neumann. But the field really took off with the publication of John von Neumann and Oskar Morgenstern’s The Theory of Games and Economic Behavior in 1944. In the late ’40s and during the ’50s this led to a surge in interest for mathematical social sciences among mathematicians and economists. It was not until the ’60s and ’70s that game theory started to play a role in biology. There is an early paper by Richard Lewontin on how classical game theory could be used in evolutionary biology (Lewontin 1961). At about the same time, William Hamilton introduced many game theoretic ideas such as the notion of an ‘‘unbeatable strategy’’ in Hamilton (1967). But the rebirth of game theory in biology is usually associated with John Maynard Smith and George Price’s introduction of the concept of an ‘‘evolutionarily stable strategy’’ (Maynard Smith and Price 1973). Since then, evolutionary biologists and ecologists have used game theory as a tool to study the evolutionary dynamics of phenotypes. This development of biological game theory has merged more recently with a renewed interest in game theory in the social sciences and in economics. Contrary to classical game theory, which is mainly based on equilibrium analysis, this more recent approach puts games in the dynamic context of evolution and learning. While by no means exhausting the breadth and the depth of the field, the articles in this issue of Biological Theory allow a glimpse at some important questions of dynamic game theory within the social and biological sciences. The outlook is interdisciplinary, with contributions from biologists, economists, mathematicians, and philosophers. The thematic issue starts off with Kevin Zollman’s ‘‘Finding Alternatives to Handicap Theory.’’ The handicap principle is an influential hypothesis in both biology and economics. It roughly states that communication is possible between a sender and a receiver who don’t have completely common interests as long as the sender must pay a cost for sending signals. Zollman presents theoretical and empirical evidence against the handicap principle and presents possible alternatives to it that allow for communication in the face of conflicting interests. Ted Bergstrom’s paper develops an important topic in theoretical biology: the effect of correlation between types on evolution. Bergstrom discusses several approaches in his contribution, ‘‘Measures of Assortativity.’’ The central concept is Wrights’s F-statistic, which is a measure of inbreeding or, alternatively, relatedness. The paper compares the F-statistic to other measures of assortative matching. It also discusses the role of assortative matching in theories of altruistic behavior. In ‘‘The Evolution of Simple Rule-Following,’’ Jeffrey Barrett uses signaling games in the style of David Lewis to design models for transitive rule-following and analyzes them with the help of computer simulations. In addition, he considers models where agents can use already evolved or learned rules in new contexts. Agents in these models can learn to infer patterns and apply them to new contexts although they only learn by simple reinforcement learning schemes. S. M. Huttegger (&) B. Skyrms Department of Logic and Philosophy of Science, University of California, Irvine, CA, USA e-mail: shuttegg@uci.edu