Network Characteristics Control Social Dilemmas in a Public Good Game: A Mechanical Framework

TL;DR

This paper introduces a mechanical framework modeling how network structures influence social dilemmas in public good games through agent-based simulations incorporating social learning and evolutionary dynamics.

Contribution

It presents a novel mechanistic model linking network characteristics to social dilemma outcomes in public good games, emphasizing the role of social ties and evolutionary processes.

Findings

Network structure affects cooperation levels in public good games.

Social ties influence strategy imitation and mutation rates.

The model applies broadly across disciplines using game theory.

Abstract

Purpose: We propose a model to present a possible mechanism for obtaining sizeable behavioural structures by simulating an agent based on the evolutionary public good game with available social learning. Methods: The model considered a population with a fixed number of players. For each round, the chosen players may contribute part of their value to a common pool. Then each player may imitate the strategy of another player, based on relative payoffs (whoever has the lower payoff adopts the strategy of the other player) and change strategy using different exploratory variables. Results: Relative payoffs are subject to incentive, including participation costs, but are also subject to mutation, the rate of which is sensitized by network characteristics (social ties). Values: The process covered by this study is of interest and is relevant across a broad range of disciplines that use game theory, including the framework of cultural evolutionary dynamics.