摘要
A Multi-Agent System ( MAS ) is a promising approach to build complex system. This paper introduces the research of the Inner-Enterprise Credit Rating MAS ( IECRMAS). To raise the rating accuracy, we not only consider the rating-target's information, but also focus on the evaluators' feature information and propose the rational rating-group formation algorithm based on an anti-bias measurement of the group. We also propose the rational rating individual, which consists of the evaluator and the assistant rating agent. A rational group formation protocol is designed to coordinate autonomous agents to perform the rating job.
A Multi-Agent System ( MAS ) is a promising approach to build complex system. This paper introduces the research of the Inner-Enterprise Credit Rating MAS ( IECRMAS). To raise the rating accuracy, we not only consider the rating-target's information, but also focus on the evaluators' feature information and propose the rational rating-group formation algorithm based on an anti-bias measurement of the group. We also propose the rational rating individual, which consists of the evaluator and the assistant rating agent. A rational group formation protocol is designed to coordinate autonomous agents to perform the rating job.
基金
This paper is supported by National Science Foundation of China under Grant No60542004