An intelligent fuzzy meeting agent for decision support system
Chang-Shing Lee, Chen-Yu Pan · 2004
An intelligent fuzzy meeting agent (IFMA) for a meeting scheduling support system (MS3) is proposed in this paper. IFMA can search and decide the suitable meeting time for the specified meeting in an organization. When a meeting host requests a meeting, Meeting Negotiation Agent (MNA) immediately sends the invitees' names to MS3 for retrieving their schedules from Group Calendar Data Base (GCDB), then MS3 will compute the possible meeting time and respond the results to MNA. Moreover, the Fuzzy Inference Agent (FIA) infers the adequate meeting time based on the information provided by MNA and Personalized Knowledge Base (PKB), and sends the computing result back to MS3. The meeting host will decide the final meeting time based on MS3 and announce the meeting information by various devices including PDA, WAP, FAX, or E-mail. Furthermore, the invitees' decisions for attending the meeting or not will be stored into meeting information knowledge base (MIKB), then the genetic learning agent (GLA) will adjust the PKB for the next meeting. By the experimental results, IFMA can work efficiently for MS3.