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We start by providing background on the study of machine behaviour and the necessarily interdisciplinary nature of this science.

We then provide a framework for the conceptualization of studies of machine behaviour.

First, various kinds of algorithms operate in our society, and algorithms have an ever-increasing role in our daily activities.

Second, because of the complex properties of these algorithms and the environments in which they operate, some of their attributes and behaviours can be difficult or impossible to formalize analytically.

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There are three primary motivations for the scientific discipline of machine behaviour.

This Review frames and surveys the emerging interdisciplinary field of machine behaviour: the scientific study of behaviour exhibited by intelligent machines.

Here we outline the key research themes, questions and landmark research studies that exemplify this field.

Machine behaviour similarly cannot be fully understood without the integrated study of algorithms and the social environments in which algorithms operate.

At present, the scientists who study the behaviours of these virtual and embodied artificial intelligence (AI) agents are predominantly the same scientists who have created the agents themselves (throughout we use the term ‘AI agents’ liberally to refer to both complex and simple algorithms used to make decisions).

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