  What computational principles underlie human pragmatic reasoning? A prominent
approach to pragmatics is the Rational Speech Act (RSA) framework, which
formulates pragmatic reasoning as probabilistic speakers and listeners
recursively reasoning about each other. While RSA enjoys broad empirical
support, it is not yet clear whether the dynamics of such recursive reasoning
may be governed by a general optimization principle. Here, we present a novel
analysis of the RSA framework that addresses this question. First, we show that
RSA recursion implements an alternating maximization for optimizing a tradeoff
between expected utility and communicative effort. On that basis, we study the
dynamics of RSA recursion and disconfirm the conjecture that expected utility
is guaranteed to improve with recursion depth. Second, we show that RSA can be
grounded in Rate-Distortion theory, while maintaining a similar ability to
account for human behavior and avoiding a bias of RSA toward random utterance
production. This work furthers the mathematical understanding of RSA models,
and suggests that general information-theoretic principles may give rise to
human pragmatic reasoning.
