Making an Example: Signalling Threat in the Evolution of Cooperation

Theodor Cimpeanu, The Anh Han

Research output: Contribution to conferencePaperpeer-review

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Social punishment has been suggested as a key
approach to ensuring high levels of cooperation and norm
compliance in one-shot (i.e. non-repeated) interactions, however
it does not usually emerge if it is not also cost-efficient. Signalling
retribution hearkens back to medieval sovereignty, insofar as the
very word for gallows in French stems from the Latin word
for power and serves as a grim symbol of the ruthlessness of
high justice. Here, we introduce the mechanism of signalling an
act of punishment and a special type of defector emerges, one
who can recognise this signal and avoid punishment by way of
fear. We describe the analytical conditions under which threat
signalling can maintain high levels of cooperation. Moreover, we
perform extensive agent-based simulations so as to confirm and
expand our understanding of the external factors that influence
the success of social punishment. We show that our suggested
mechanism catalyses cooperation, even when signalling is costly
or when punishment would be impractical. We observe the
preventive nature of advertising retributive acts and we contend
that the resulting social prosperity is a desirable outcome in the
contexts of AI and multi-agent systems. To conclude, we argue
that fear acts as an effective stimulus to pro-social behaviour.
Original languageEnglish
Publication statusAccepted/In press - 2020
Event2020 IEEE Congress on Evolutionary Computation (CEC) - Glasgow, United Kingdom
Duration: 19 Jul 202024 Jul 2020


Conference2020 IEEE Congress on Evolutionary Computation (CEC)
Abbreviated titleCEC2020
Country/TerritoryUnited Kingdom
Internet address


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