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

Author:

Bohn Manuel1ORCID,Liebal Katja2ORCID,Oña Linda3,Tessler Michael Henry4ORCID

Affiliation:

1. Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany

2. Institute of Biology, Leipzig University, 04103 Leipzig, Germany

3. Naturalistic Social Cognition Group, Max Planck Institute for Human Development, 14195 Berlin, Germany

4. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA

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’.

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

Reference101 articles.

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