Visualizing multi‐agent collaboration for classification of information

Abstract

IntroductionA multi-agent framework is useful for studying complex social and information systems. By definition, an agent is a computer program capable of autonomous action to meet its designed objectives in certain environment (Jennings & Wooldridge, 1998). In multi-agent systems, agents are treated as distributed peers that have scattered intelligence and can collaborate with each other to do certain tasks. Research on information retrieval has relied upon multi-agent technologies for better understanding of collective retrieval operations in distributed environments. This also responds to the increasing computational demands for retrieval and offers a great potential of scalability.However, a common challenge in the use of agent technology involves the monitoring of agent activities. User interfaces should be designed to convey information about real-time dynamics in the systems. Information visualization, which attempts to facilitate information communication through visual representations (Hearst, 1999), is potentially useful in the agent-based research. Jennings and Wooldridge (1998) points out that visualization is particularly important for the development and use of agent technology because it is critical, though difficult, to know what is happening in asynchronous, concurrent systems. A few agent software frameworks have specialized features that support information visualization. However, it remains unclear what type of information is commonly useful for visualization and applicable across systems.