 The standard solution concept of game theory is Nash equilibrium. A Nash equilibrium of a signaling game is a pair of strategies \(\langle\)S\(^*\),R\(^*\)\(\rangle\) which has the property that neither the sender nor the receiver could increase his or her expected utility by unilateral deviation. Thus, S\(^*\) is a best response to R\(^*\) and R\(^*\) is a best response to S\(^*\). There are plenty of refinements of Nash equilibrium in the game-theoretic literature. Moreover, there are alternatives to equilibrium analyses, the two most prominent of which are: (i) explicit formalizations of agents’ reasoning processes, such as is done in epistemic game theory (e.g., Perea 2012), and (ii) variants of evolutionary game theory (e.g., Sandholm 2010) that study the dynamic changes in agents’ behavioral disposition under gradual optimization procedures, such as by imitation or learning from parents. These issues are relevant for applications to linguistic pragmatics as well, as we will demonstrate presently with the example of M-implicatures/Horn’s division of pragmatic labor.