A multi-agent game for studying human decision-making

Abstract

Understanding how human beings delegate tasks to trustees when presented with reputation information is important for building trust models for human-agent collectives. However, there is a lack of suitable platforms for building large scale datasets on this topic. We describe a demonstration of a multi-agent game for training students in the practice of Agile software engineering. Through interacting with agent competitors in the game, the behavior data related to users' decision-making process under uncertainty and resource constraints are collected in an unobtrusive fashion. These data may provide multi-agent trust researchers with new insight into the human decision-making process, and help them benchmark their proposed models.