Visualizing multi-agent collaboration for classification of information



Agent-based simulation is a popular technology for studying social and information systems. Information visualization in such simulations is potentially useful for communicating real time information but involves several levels of challenges. It remains unclear what patterns of agent activities are useful for visualization. To motivate and investigate potentially useful patterns for visualization, we identified four factors: 1) Agent Involvement; 2) Dominant Player; 3) Learning and Adaptation; and 4) Influence of Task and Content Stream. To demonstrate the usefulness of the factors, we operationalized them to permit analysis and visualization in the context of a problem involving coordination among agents conducting document classification.