Evolutionary Game Analysis of Human-Computer Interaction Based on System Dynamics and Fuzzy Inference
Xin Lu, Jianbin Guo, Shengkui Zeng, Haiyang Che · 2023
The Ethiopian Airlines Boeing 737 MAX crash invited attention to the potential conflicts during human-computer interaction (HCI) caused by the introduction of intelligent-assisted decision-making systems, which can impact the safety of the human-machine system. To understand the dynamics of this interaction, this study suggests a new approach combining evolutionary game theory, system dynamics, and fuzzy inference that can model and analyze HCI. Evolutionary game theory is suitable for describing the HCI process owing to its nature of cooperation and game between operators and intelligent decision-making systems. By modeling the HCI as an evolutionary game process, we can identify strategies, comprehend the dynamics and evolution of each strategy, and predict the outcomes under different scenarios. Further, system dynamics is employed to establish the utilization, maintenance, and enhancement process of human-machine systems and to determine the relevant parameters in evolutionary game models. Finally, fuzzy interface is employed to tackle the complexity and uncertainty in the model. The results indicate that this proposed approach can offer valuable insights into the dynamics of HCI and facilitate the design of better human-computer systems.