Drivers of cooperation in social dilemmas on higher-order networks

TL;DR

This paper introduces a higher-order network framework for multi-player social dilemmas, capturing complex group interactions and revealing how multilevel nested interactions promote cooperation beyond traditional models.

Contribution

It presents a novel higher-order network model incorporating multi-dimensional strategies and multilevel interactions, advancing understanding of cooperation in structured populations.

Findings

Nested multilevel interactions enhance cooperation.

Higher-order models outperform traditional pairwise frameworks.

Key drivers of cooperation are identified in complex social dilemmas.

Abstract

Understanding cooperation in social dilemmas requires models that capture the complexity of real-world interactions. While network frameworks have provided valuable insights to model the evolution of cooperation, they are unable to encode group interactions properly. Here, we introduce a general higher-order network framework for multi-player games on structured populations. Our model considers multi-dimensional strategies, based on the observation that social behaviours are affected by the size of the group interaction. We investigate dynamical and structural coupling between different orders of interactions, revealing the crucial role of nested multilevel interactions, and showing how such features can enhance cooperation beyond the limit of traditional models with uni-dimensional strategies. Our work identifies the key drivers promoting cooperative behaviour commonly observed in real-world group social dilemmas.