Author :
Sugawara, Toshiharu ; Akashi, Osamu ; Kurihara, Satoshi ; Sato, Shin Ya
Abstract :
This paper proposes an organizational information maintenance component (OIMC) that autonomously maintains organizational information (OI) in a multiagent system. Organization-related information is used to enable appropriate/satisfiable collaborations. It is strongly required in multi-agent (MA) applications that the agent, which is a delegate of some real-world entity or concept such as service, human, company and their relation (such as WARREN system whose agents represent customers, fund managers, technical analysts, and securities companies) has accurate and latest OI. There are also other MA systems that should take into account agent´s characteristics, such as honesty, reliability, strictness (for rating their task quality) and trustworthiness, for task allocations. The OI is, furthermore, likely to change over time because an agent may enter or exit a group, because data must adapt to human relations in the real world, and because data in their information servers becomes obsolete or is updated. Thus, agents must maintain their OI even while they are not active. However, since creating and maintaining organizational models of agents are not easy tasks, cooperative reasoners, planners, and schedulers with the mechanism for the OI maintenance are complicated and difficult to implement and maintain in actual applications. The proposed component, which works like a secretary and operates independent from the local agent and by exchanging OI, provides the general framework for maintaining an updated organizational model. The agents can ask organization-related queries to this component and can reflect the current OI to its inference
Keywords :
inference mechanisms; multi-agent systems; planning (artificial intelligence); WARREN system; agent collaboration; cooperative reasoners; information servers; multiagent system; organizational information maintenance component; planning; reasoning; schedulers; task allocations; Collaboration; Humans; Multiagent systems; Quality management; Scheduling; Security;