Collaborative Decision based on Rough Set in MultiAgent Intelligent Decision Support System

Intelligent Decision Support System is a human-computer interaction information system and it can assist decision-maker to make right decision. In this paper, Multi-Agent is used in Intelligent Decision Support System. In Multi-Agent System, finding cooperative agents becomes a key issue because the knowledge and problem-solving capability of an individual agent is limited. An approach to find collaborative agents in simplified acquaintance model based on the degree of commitment is proposed. At the same time, an effective attribute alternation algorithm is designed use of decision tree and rough set. The principles of the simplest decision tree is offered. The method is applicable for cooperative decision among agents and can help to complete complicated works in Multi-Agent System. Intelligent Decision Support System based on MultiAgent can be used to solve large-scale complex problem.