Systems Engineering and Electronics ›› 2022, Vol. 44 ›› Issue (8): 2540-2553.doi: 10.12305/j.issn.1001-506X.2022.08.19

• Systems Engineering • Previous Articles     Next Articles

A stimulus-response learning model for Agent-based system process A-GERT network

Zhigeng FANG1,2, Yuexin XIA1,2,*, Jingru ZHANG1,2, Yi XIONG1,2, Jingyi CHEN1,2   

  1. 1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China
    2. Institute of Grey System, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China
  • Received:2021-07-15 Online:2022-08-01 Published:2022-08-24
  • Contact: Yuexin XIA

Abstract:

In view of the graphic evaluation and review technique (GERT) network applied in the decision-making process of system activities without considering the learning initiative of network nodes themselves, an A-GERT network model is developed based on Agent technology and stimulus-response model. Firstly, the framework of the A-GERT network is developed, and through the utility function of network transmission, the A-GERT network with feedback mechanism is designed. Then, we employ the adaptive advantages of the stimulus-response model to design the learning equation, and measure the stimulus intensity with the expected probability and expected time of the GERT network, so as to further expand the stimulus-response model. Finally, the learning steps of network intelligent decision nodes are given, and an example of innovation technology development system is given. The results show the effectiveness and practicability of the proposed method.

Key words: graphic evaluation and review technique (GERT), Agent technology, complex adaptive system, stimulus-response model, adaptive learning

CLC Number: 

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