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Emergent language: a survey and taxonomy
Journal article   Open access   Peer reviewed

Emergent language: a survey and taxonomy

Jannik Peters, Constantin Waubert de Puiseau, Hasan Tercan, Arya Gopikrishnan, Gustavo Adolpho Lucas de Carvalho, Christian Bitter and Tobias Meisen
Autonomous agents and multi-agent systems, v 39(1), 18
01 Jun 2025
DOI: https://doi.org/10.1007/s10458-025-09691-y
url
https://doi.org/10.1007/s10458-025-09691-yView
Published, Version of Record (VoR) Open

Abstract

Automation & Control Systems Computer Science, Artificial Intelligence Science & Technology Computer Science Technology
The field of emergent language represents a novel area of research within the domain of artificial intelligence, particularly within the context of multi-agent reinforcement learning. Although the concept of studying language emergence is not new, early approaches were primarily concerned with explaining human language formation, with little consideration given to its potential utility for artificial agents. In contrast, studies based on reinforcement learning aim to develop communicative capabilities in agents that are comparable to or even superior to human language. Thus, they extend beyond the learned statistical representations that are common in natural language processing research. This gives rise to a number of fundamental questions, from the prerequisites for language emergence to the criteria for measuring its success. This paper addresses these questions by providing a comprehensive review of relevant scientific publications on emergent language in artificial intelligence. Its objective is to serve as a reference for researchers interested in or proficient in the field. Consequently, the main contributions are the definition and overview of the prevailing terminology, the analysis of existing evaluation methods and metrics, and the description of the identified research gaps.

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