关键词: Agent, 多属性决策, 综合权重, 感知价值, 前景理论, 实验教学

Abstract:

In business intelligence, Agent-based automatic negotiation, which uses various artificial intelligence advantages of Agent to simulate people’s actual business negotiation, has been paid more and more attention, among which multi-attribute decision making is particularly important. In view of the current situation of insufficient research on the weight and perceived value, firstly, it uses the hesitating fuzzy number and makes a new attribute classification. After establishing the corresponding hesitating fuzzy evaluation matrix and the evaluation value specification, it constructs the corresponding subjective weight algorithm. Secondly, combining the objective optimization model and Lagrange function, the corresponding objective weight algorithm is constructed, and then an improved comprehensive weight calculation method is proposed. Then based on prospect theory, it introduces loss aversion factor, proposes to the positive and negative ideal point as a reference point, sets up corresponding algorithm property and the distance from the positive and negative ideal solution is calculated, and uses it as a new parameters to perceived value function, and then puts forward the comprehensive perceived value function based on improved overall dominance algorithm, finally constructs the multiple attribute decision making model based on Agent. Finally, taking the purchase negotiation of experimental teaching equipment in a university as an example, the sensitivity analysis and comparative analysis with relevant research results verify that the model can help Agent make more rapid, reasonable and effective decisions.

Key words: Agent, multi-attribute decision making, comprehensive weight, perceived value, prospect theory, experimental teaching