Great ape communication as contextual social inference: a computational modelling perspective

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Great ape communication as contextual social inference: a computational modelling perspective. / Bohn, Manuel; Liebal, Katja; Oña, Linda et al.
in: Philosophical Transactions of the Royal Society B: Biological Sciences, Jahrgang 377, Nr. 1859, 20210096, 12.09.2022.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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@article{ed837fdeda574c42b71fc63081bb2fcf,
title = "Great ape communication as contextual social inference: a computational modelling perspective",
abstract = "Human communication has been described as a contextual social inference process. Research into great ape communication has been inspired by this view to look for the evolutionary roots of the social, cognitive and interactional processes involved in human communication. This approach has been highly productive, yet it is partly compromised by the widespread focus on how great apes use and understand individual signals. This paper introduces a computational model that formalizes great ape communication as a multi-faceted social inference process that integrates (a) information contained in the signals that make up an utterance, (b) the relationship between communicative partners and (c) the social context. This model makes accurate qualitative and quantitative predictions about real-world communicative interactions between semi-wild-living chimpanzees. When enriched with a pragmatic reasoning process, the model explains repeatedly reported differences between humans and great apes in the interpretation of ambiguous signals (e.g. pointing or iconic gestures). This approach has direct implications for observational and experimental studies of great ape communication and provides a new tool for theorizing about the evolution of uniquely human communication. This article is part of the theme issue 'Revisiting the human 'interaction engine': comparative approaches to social action coordination'.",
keywords = "communication, computational modelling, evolution, primates, social cognition, Psychology",
author = "Manuel Bohn and Katja Liebal and Linda O{\~n}a and Tessler, {Michael Henry}",
note = "Publisher Copyright: {\textcopyright} 2022 The Authors.",
year = "2022",
month = sep,
day = "12",
doi = "10.1098/rstb.2021.0096",
language = "English",
volume = "377",
journal = "Philosophical Transactions of the Royal Society B: Biological Sciences",
issn = "0962-8436",
publisher = "Royal Society Publishing",
number = "1859",

}

RIS

TY - JOUR

T1 - Great ape communication as contextual social inference

T2 - a computational modelling perspective

AU - Bohn, Manuel

AU - Liebal, Katja

AU - Oña, Linda

AU - Tessler, Michael Henry

N1 - Publisher Copyright: © 2022 The Authors.

PY - 2022/9/12

Y1 - 2022/9/12

N2 - Human communication has been described as a contextual social inference process. Research into great ape communication has been inspired by this view to look for the evolutionary roots of the social, cognitive and interactional processes involved in human communication. This approach has been highly productive, yet it is partly compromised by the widespread focus on how great apes use and understand individual signals. This paper introduces a computational model that formalizes great ape communication as a multi-faceted social inference process that integrates (a) information contained in the signals that make up an utterance, (b) the relationship between communicative partners and (c) the social context. This model makes accurate qualitative and quantitative predictions about real-world communicative interactions between semi-wild-living chimpanzees. When enriched with a pragmatic reasoning process, the model explains repeatedly reported differences between humans and great apes in the interpretation of ambiguous signals (e.g. pointing or iconic gestures). This approach has direct implications for observational and experimental studies of great ape communication and provides a new tool for theorizing about the evolution of uniquely human communication. This article is part of the theme issue 'Revisiting the human 'interaction engine': comparative approaches to social action coordination'.

AB - Human communication has been described as a contextual social inference process. Research into great ape communication has been inspired by this view to look for the evolutionary roots of the social, cognitive and interactional processes involved in human communication. This approach has been highly productive, yet it is partly compromised by the widespread focus on how great apes use and understand individual signals. This paper introduces a computational model that formalizes great ape communication as a multi-faceted social inference process that integrates (a) information contained in the signals that make up an utterance, (b) the relationship between communicative partners and (c) the social context. This model makes accurate qualitative and quantitative predictions about real-world communicative interactions between semi-wild-living chimpanzees. When enriched with a pragmatic reasoning process, the model explains repeatedly reported differences between humans and great apes in the interpretation of ambiguous signals (e.g. pointing or iconic gestures). This approach has direct implications for observational and experimental studies of great ape communication and provides a new tool for theorizing about the evolution of uniquely human communication. This article is part of the theme issue 'Revisiting the human 'interaction engine': comparative approaches to social action coordination'.

KW - communication

KW - computational modelling

KW - evolution

KW - primates

KW - social cognition

KW - Psychology

UR - http://www.scopus.com/inward/record.url?scp=85134902339&partnerID=8YFLogxK

U2 - 10.1098/rstb.2021.0096

DO - 10.1098/rstb.2021.0096

M3 - Journal articles

C2 - 35876204

AN - SCOPUS:85134902339

VL - 377

JO - Philosophical Transactions of the Royal Society B: Biological Sciences

JF - Philosophical Transactions of the Royal Society B: Biological Sciences

SN - 0962-8436

IS - 1859

M1 - 20210096

ER -

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