Abstract:

We introduce a generalization of classical game theory wherein each player has a fixed “language of preference”: a player can prefer one state of the world to another iff they can describe the difference between the two in this language. The expressiveness of the language therefore plays a crucial role in determining the parameters of the game. By choosing appropriately rich languages, this framework can capture classical games as well as various generalizations thereof (e.g. psychological games, reference-dependent preferences, and Bayesian games). On the other hand, coarseness in the language---cases where there are fewer descriptions than there are actual differences to describe---offers insight into some long-standing puzzles of human decision-making. The Allais paradox, for instance, can be resolved simply and intuitively using a language with coarse beliefs: that is, by assuming that probabilities are represented not on a continuum, but discretely, using finitely-many “levels” of likelihood (e.g. ”no chance”, “slight chance”, “unlikely”, “likely”, etc.).

Many standard solution concepts from classical game theory can be imported into the language-based framework by taking their /epistemic characterizations/ as definitional. In this way, we obtain natural generalizations of Nash equilibrium, correlated equilibrium, and rationalizability. We show that there are language-based games that admit no Nash equilibria using a simple example where one player wishes to surprise her opponent. By contrast, the existence of rationalizable strategies can be proved under mild conditions.

This is joint work with Joe Halpern and Rafael Pass.