Collective Intelligent Decision Making Method Based on Rationality Negotiation
Wentao Luo, Feng Pingfa, Zhang Jianfu, Dingwen Yu, Zhijun Wu, Haochen Liu · Journal of Physics Conference Series · 2020
Abstract Collective intelligence without considering the rationality of the decision-making process often leads to unreasonable decisions, which brings immeasurable losses to intelligent system. To solve it, a collective intelligent decision-making method based on rationality negotiation is proposed. Each individual with decision-making right is endowed with wisdom by the adapted Q learning algorithm, so that each individual has the perceived ability and individual motivation. Rationality Negotiation Model algorithm is proposed to select a rational decision of group, which reflects collective motivation of group. Then the decision result generated by the collective motivation is transformed into knowledge feedback to each individual, so that the individual also learn the collective motivation. Finally with the repeated iterative optimization, individual action becomes reasonable in the long run. A case is studied based on industrial enterprises making decision in the face of unexpected situations influence production process. The actual verification shows that the proposed decision-making scheme for intelligent system is reasonable.