Title of article :
ADAPTIVE EXCEPTION MONITORING AGENTS FOR MANAGEMENT BY EXCEPTIONS
Author/Authors :
Liu، Rey-Long نويسنده , , Shih، Meng-Jung نويسنده , , Kao، Yu-Fen نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2001
Abstract :
Management by exceptions (MBE) is an effective management strategy in many domains. It suggests that managers focus on important jobs (e.g., planning and decision-making) without being involved in the tedious monitoring of exceptions (e.g., a critical item whose current status violates some regulations). Once an exception is detected, the managers are notified to respond to the exception promptly. Therefore, exception monitoring is the key to realize the idea of MBE. An exception monitoring system should detect exceptions in a timely manner for the managers. It should also control the extra loading it incurs to related information servers (e.g., database management systems) and the Intranet, which are fundamental backbones for information processing in businesses. In this paper, a multiagent paradigm Adaptive Agents for Management by Exceptions (AAMBE) is proposed for exception monitoring. The agents adapt to the environment by learning to work together to achieve timely detection of exceptions. An experiment to investigate the performance of AAMBE is conducted by simulating real-world operations of financial management in merchandising trades. Empirical and theoretical analyses show that AAMBE may detect more exceptions in a timelier manner by incurring less extra loading to the related information servers and the Intranet.
Keywords :
Estimation , Kinetic method , Benzyl alcohol , Kinetics
Journal title :
Applied Artificial Intelligence
Journal title :
Applied Artificial Intelligence