On salience and signaling in sender–receiver games: partial pooling, learning, and focal points

Abstract

I introduce an extension of the Lewis-Skyrms signaling game, analysed from a dynamical perspective via simple reinforcement learning. In David Lewis' (1969) conception of a signaling game, salience is offered as an explanation for how individuals may come to agree upon a linguistic convention. Brian Skyrms (2010) offers a dynamic explanation of how signaling conventions might arise presupposing no salience whatsoever. The extension of the atomic signaling game examined here-which I will refer to as a salience gameintroduces a variable parameter into the atomic signaling game which allows for degrees of salience, thus filling in the continuum between Skyrms' and Lewis' models. The model does not presuppose any salience at the outset, but illustrates a process by which accidentally evolved salience is amplified, to the benefit of the players. It is shown that increasing degrees of salience allow populations to avoid sub-optimal pooling equilibria and to coordinate upon conventions more quickly.

Sifting the Signal from the Noise

“…One could go further and consider cases in which the different features have different numbers of possible values. This would of course make it more challenging to characterize the mutual information of the various features in a transparent way.20 See(LaCroix [2020a]) for a recent study of the effect a 'salience parameter' has on learning in Lewis-Skyrms signalling games.…”

Self-organizing social systems: boundaries of cooperation and coordination

“…the robustness of the evolution of meaning by varying assumptions like population size [143], randomness of pairing [175], initial strategy randomness [112], and the probability of states [88]. For the most part, these studies find a strong convergence to successful signaling across a wide variety of settings, learning rules, and evolutionary dynamics [92; 113].…”