Machine Behaviour

doi:10.1017/9781108939010.021

16 - Machine Behaviour

from Part III - Algorithmic Behaviour

Published online by Cambridge University Press: 29 May 2026

Patrick Henz

Edited by

Ganna Pogrebna and

Thomas T. Hills

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Ganna Pogrebna: Affiliation:
The Alan Turing Institute
Thomas T. Hills: Affiliation:
University of Warwick

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Summary

Machines are becoming more autonomous and intelligent, capable of making decisions and interacting with their environment. As they become more ubiquitous in our daily lives, it becomes increasingly important to understand and model their behaviour. This chapter will discuss the concept of machine behaviour and its importance in various fields, including artificial intelligence, robotics and human–computer interaction. The chapter starts by defining machine behaviour and providing an overview of its key characteristics. It will then explore the different approaches to modelling and understanding machine behaviour, including rule-based systems, statistical models and deep learning techniques. The chapter also covers the challenges and limitations of modelling machine behaviour, including the black box problem, interpretability and ethics. It also focuses on the applications of machine behaviour in various domains, such as autonomous vehicles, robotics and cybersecurity. The chapter will highlight how machine behaviour models can help in improving the performance, safety and security of these systems. The chapter discusses the future of machine behaviour and its potential impact on society. The chapter will explore the ethical implications of autonomous machines, including issues of responsibility, accountability and transparency. It will also discuss the need for interdisciplinary research in machine behaviour.

Keywords

machine behaviour AI machine learning human–machine interaction autonomous systems

Information

Type: Chapter
Information: The Cambridge Handbook of Behavioural Data Science , pp. 287 - 305
DOI: https://doi.org/10.1017/9781108939010.021 [Opens in a new window]
Publisher: Cambridge University Press
Print publication year: 2026

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