Human/unmanned-aerial-vehicle team collaborative decision-making with limited intervention

In view of the characteristics of Leader-Follower heterogeneous multi-platform system for the human/unmanned aerial vehicle team which are hierarchical and distributed structure, decision-making information decentralization and communication constraints, the collaborative decision-making mechanism with limited intervention based on the combination of agent-based fuzzy cognitive map (ABFCM) and dynamic fuzzy cognitive map (DFCM) is presented. In the proposed approach, hierarchical autonomous decision-making model for Follower platform is developed in order to make the Follower able to interact with external environment well and reflect the autonomous decision-making dynamics. Three intervention strategies under different conditions are designed for Leader platform to meet the requirements of different decision levels. Meanwhile these strategies reflect the limitation of intervention processes. Simulation results show that intervention-limited collaborative decision-making mechanism can adapt to dynamic changes in the external environment and make full use of Follower platform's autonomous decision-making ability. Hierarchical limited interventions can reduce the control workload of Leader and ensure the effectiveness and feasibility of decision-making as well. This work also provides a theoretical basis and methodology support to solve other similar collaborative decision-making problem in complex systems.