Roland Mühlenbernd

I present a game-theoretical multi-agent system to simulate the evolutionary process responsible for the pragmatic phenomenon division of pragmatic labour (DOPL), a linguistic convention emerging from evolutionary forces. Each agent is positioned on a toroid lattice and communicates via signaling games , where the choice of an interlocutor depends on the Manhattan distance between them. In this framework I compare two learning dynamics: reinforcement learning (RL) and belief learning (BL). An agent’s experiences from previous plays influence his communication behaviour, and RL agents act in a non-rational way whereas BL agents display a small degree of rationality by using best response dynamics . The complete system simulates an evolutionary process of communication strategies, which agents can learn in a structured spatial society. The significant questions are: what circumstances could lead to an evolutionary process that doesn’t result in the expected DOPL convention; and to what extent is interlocutor rationality necessary for the emergence of a society-wide convention à la DOPL?

To depict the mechanisms that have enabled the emergence of semantic conventions, philosophers and researchers particularly access a game-theoretic model: the signaling game. In this article I argue that this model is also quite appropriate to analyze not only the emergence of a semantic convention, but also its change. I delineate how the application of signaling games helps to reproduce and depict mechanisms of semantic change. For that purpose I present a model that combines a signaling game with innovative reinforcement learning; in simulation runs I conduct this game repeatedly within a multi-agent setup, where agents are arranged in social network structures. The results of these runs are contrasted with an attested theory from sociolinguistics: the ‘weak tie’ theory. Analyses of the produced data target a deeper understanding of the role of environmental variables for the promotion of semantic change or solidity of semantic conventions.

Politeness in conversation is a fascinating aspect of human interaction that directly interfaces language use and human social behavior more generally. We show how game theory, as a higher-order theory of behavior, can provide the tools to understand and model polite behavior. The recently proposed responsibility exchange theory :313–344, 2019) describes how the polite communications of thanking and apologizing impact two different types of an agent’s social image: warmth and competence. Here, we extend this approach in several ways, most importantly by adding a cultural-evolutionary dynamics that makes it possible to investigate the evolutionary stability of politeness strategies. Our analysis shows that in a society of agents who value status-related traits over reciprocity-related traits, both the less and the more polite strategies are maintained in cycles of cultural-evolutionary change.

In this paper we study AGM contraction and revision of rules using input/output logical theories. We replace propositional formulas in the AGM framework of theory change by pairs of propositional formulas, representing the rule based character of theories, and we replace the classical consequence operator Cn by an input/output logic. The results in this paper suggest that, in general, results from belief base dynamics can be transferred to rule base dynamics, but that a similar transfer of AGM theory change to rule change is much more problematic. First, we generalise belief base contraction to rule base contraction, and show that two representation results of Hansson still hold for rule base contraction. Second, we show that the six so-called basic postulates of AGM contraction are consistent only for some input/output logics, but not for others. In particular, we show that the notorious recovery postulate can be satisfied only by basic output, but not by simple-minded output. Third, we show how AGM rule revision can be defined in terms of AGM rule contraction using the Levi identity. We highlight various topics for further research.

In Lewisean signaling games with common interests, perfect signaling strategies have been shown to be optimal in terms of communicative success and evolutionary fitness. However, in signaling game models that involve contextual cues, ambiguous signaling strategies can match up to or even outperform perfect signaling. For a minimalist example of such a context signaling game, I will show that three strategy types are expected to emerge under evolutionary dynamics: perfect signaling, partial ambiguity and full ambiguity. Moreover, I will show that partial ambiguity strategies are the most expected outcome and have the greatest basin of attraction among these three types when sender and receiver costs are arbitrarily small or similar. I will demonstrate that the evolutionary success of partial ambiguity is due to being risk dominant, which points to a better compatibility with other strategy types.