Learning with neighbours: Emergence of convention in a society of learning agents

Synthese 183 (S1):87-109 (2011)
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Abstract

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?

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Citations of this work

The Evolution of Compositionality in Signaling Games.Michael Franke - 2016 - Journal of Logic, Language and Information 25 (3-4):355-377.
Bidirectional Optimization from Reasoning and Learning in Games.Michael Franke & Gerhard Jäger - 2012 - Journal of Logic, Language and Information 21 (1):117-139.
Evolutionary Explanations of Simple Communication: Signalling Games and Their Models.Travis LaCroix - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (1):19-43.
Game Theoretic Pragmatics.Michael Franke - 2013 - Philosophy Compass 8 (3):269-284.

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