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Synthese

, Volume 183, Supplement 1, pp 87–109 | Cite as

Learning with neighbours

Emergence of convention in a society of learning agents
  • Roland MühlenberndEmail author
Article

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?

Keywords

Multi-agent system Division of pragmatic labour Signaling games Learning dynamics Communication strategies Simulation of an evolutionary process 

Abbreviations

DOPL

Division of pragmatic labour

BL

Belief learning

NE

Nash equilibrium

RD

Replicator dynamics

RL

Reinforcement learning

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.University of TübingenTübingenGermany

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