Adaptive Payoff-driven Interaction in Networked Snowdrift Games

TL;DR

This paper introduces an adaptive network model for the snowdrift game, showing how dynamic restructuring of social ties influences cooperation levels and network topology, especially under extreme cost-benefit conditions.

Contribution

It presents a novel adaptive network framework with asymmetric disassociation tendencies, demonstrating its effectiveness in promoting cooperation and shaping network structure.

Findings

Adaptive networks promote robust cooperation or defection states.

Dynamic rewiring influences network degree distribution.

Cooperators expand neighborhoods to resist defection invasion.

Abstract

In social dilemmas, most interactions are transient and susceptible to restructuring, leading to continuous changes in social networks over time. Typically, agents assess the rewards of their current interactions and adjust their connections to optimize outcomes. In this paper, we introduce an adaptive network model in the snowdrift game to examine dynamic levels of cooperation and network topology, involving the potential for both the termination of existing connections and the establishment of new ones. In particular, we define the agent's asymmetric disassociation tendency toward their neighbors, which fundamentally determines the probability of edge dismantlement. The mechanism allows agents to selectively sever and rewire their connections to alternative individuals to refine partnerships. Our findings reveal that adaptive networks are particularly effective in promoting a robust evolution toward states of either pure cooperation or complete defection, especially under conditions of extreme cost-benefit ratios, as compared to static network models. Moreover, the dynamic restructuring of connections and the distribution of network degrees among agents are closely linked to the levels of cooperation in stationary states. Specifically, cooperators tend to seek broader neighborhoods when confronted with the invasion of multiple defectors.