Conflict and cooperation: a systematic exploration

Leonardo Castro Gonzalez ^1* Rodrigo Leal-Cervantes ^2* Ekkehard Ernst ²

• ¹ The Alan Turing Institute, London, United Kingdom
• ² International Labour Organization, Geneva, Geneva, Switzerland

Economic cooperation is inherently dynamic, with agents adjusting the frequency, mechanisms, and intensity of their interactions over time. When scaling this behaviour to a large number of agents, we obtain a complex cooperation network where interaction dynamics influence the system's macro-state. This study looks into how network topologies impact the survival of economic cooperation. Specifically, we explore the effect of topologies in sustaining cooperation through the survival of a "saving trait", a feature that promotes cooperative interactions among agents. In our model, similar to a Stag Hunt (SH) game with memory, agents adapt their saving traits based on the profitability of past interactions with others. We simulate the game on seven distinct network structures sourced from the public repository Netzschleuder and analyse the robustness of the saving trait under topological shocks. Of the seven networks studied, we find that two of them sustain different behaviours with respect to the initial conditions. From the seven studied networks, we recover the two equilibria dynamics from the SH game for four of them. For the remaining three, we obtain stable mixed states. These findings show that network topology affects the survival of the saving trait and its vulnerability to widespread topological shocks(over 25% of edges shifted or added). This work contributes to the interdisciplinary effort to understand economic cooperation by integrating insights from network science, game theory, and the social sciences.