The Impact of Information Availability on Trust Emergence in an Agent-Based Model of Stag Hunt

Abstract

Trust is crucial in the success of cooperative behavior within multi-agent systems, particularly in situations requiring coordination under uncertainty. Stag Hunt is a coordination game that presents agents with a choice between cooperating for a riskier, high-reward option or defecting for a guaranteed but modest reward.

While other models of the stag hunt include agents with mixed strategies, dynamic networks, and differing levels of information availability, this model in NetLogo attempts to incorporate all of these elements.

In this simulation, agents repeatedly play Stag Hunt with others under three conditions: (1) Amnesia, where agents lack memory of past interactions; (2) Experience, where agents track the trustworthiness of previous partners; and (3) Common Knowledge, where all agents possess knowledge of every other agent's trustworthiness. In the latter two models, each agent's trustworthiness dynamically updates based on their cooperation or defection. Agents decide whether or not they want to play Stag Hunt with potential partners based on these reputation-weighted probabilities. This decision is distinct from the choice to cooperate or defect during the Stag Hunt.

As information availability increases, unreliable agents perform worse: the bottom 40% of agents earn 28% of total energy in Amnesia, 14.6% in Experience, and just 1.1% in Common Knowledge. Their share of total interactions similarly drops from 45% to 3%. Meanwhile, the proportion of interactions resulting in successful stag hunts increases with more information, indicating higher coordination.

These findings suggest that greater information availability punishes unreliability and promotes efficient cooperation, leading to better overall coordination.