Aims and objectives

The aim of this course is to introduce participants to concepts and results in evolutionary game theory of relevance for economics.
Evolutionary game theory was pioneered by John Maynard Smith and George Price in an article in Nature in 1973. Inspired by non-cooperative game theory, they suggested a solution concept for evolutionary biology, namely, evolutionary stability of strategies. That approach, which generalizes Darwin’s natural selection paradigm from “perfect competition” to “imperfect competition” in the survival of the fittest, has spurred a large literature not only in biology but also in many behavioral and social sciences including economics.
In his 1950 Ph.D. thesis (in mathematics at Princeton university), John Nash proposed two interpretations of his equilibrium concept, one rationalistic (or epistemic) and one population-statistical (or evolutionary). Instead of imagining that the interaction in question takes place exactly once under common knowledge between perfectly rational individuals, as in the rationalistic interpretation, the population-statistical interpretation is that the interaction takes place recurrently in random matchings between boundedly rational individuals from large populations, one population for each player role in the game. This interpretation is very close to that made in evolutionary game theory, and it turns out that it has behavioral implications for Nash equilibrium and beyond.

This course will introduce the participants to such concepts as evolutionary and neutral stability of strategies, the single-population replicator dynamic, deterministic and stochastic multi-population dynamics, and approaches to preference evolution, that is, models in which individuals act rationally given their preferences, but preferences evolve in the population according to how well individuals with those preferences do in the interactions at hand. Key results in this broad literature will be presented and discussed, in particular, their implications for rational behavior and for point- and set-valued solution concepts in non-cooperative game theory. Time allowing, we will also briefly discuss pre-play communication, language, social conventions and norms.