The evolution of manipulative cheating

Abstract
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Abstract

A social cheat is typically assumed to be an individual that does not perform a cooperative behaviour, or performs less of it, but can still exploit the cooperative behaviour of others. However, empirical data suggests that cheating can be more subtle, involving evolutionary arms races over the ability to both exploit and resist exploitation. These complications have not been captured by evolutionary theory, which lags behind empirical studies in this area. We bridge this gap with a mixture of game-theoretical models and individual-based simulations, examining what conditions favour more elaborate patterns of cheating. We found that as well as adjusting their own behaviour, individuals can be selected to manipulate the behaviour of others, which we term 'manipulative cheating'. Further, we found that manipulative cheating can lead to dynamic oscillations (arms races), between selfishness, manipulation, and suppression of manipulation. Our results can help explain both variation in the level of cheating, and genetic variation in the extent to which individuals can be exploited by cheats.

Data availability

All results are generated using C and Python. The codes and data used for this study are available at: https://github.com/mingpapilio/Codes_Manipulative_Cheat

Article and author information

Author details

Ming Liu

Department of Biology, University of Oxford, Oxford, United Kingdom

For correspondence
ming.liu@zoo.ox.ac.uk

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-5170-8688
Stuart Andrew West

Department of Biology, University of Oxford, Oxford, United Kingdom

Competing interests
The authors declare that no competing interests exist.
Geoff Wild

University of West Ontario, University of West Ontario, Ontario, Canada

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-7821-7304

Funding

European Research Council (Horizon 2020 Advanced Grant 834164)

Ming Liu
Stuart Andrew West

Ministry of Education (Oxford-Taiwan Graduate Scholarships)

Ming Liu

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.