可信自治系统的计算红队

Jiangjun Tang, George Leu, H. Abbass
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摘要

本章提出了一个采用计算红队的影响和塑造模型。该模型使用仿真环境进行了演示和计算验证,其中社会影响和塑造应用于人工社会。在经典的Boids模型中加入了态势感知网络拓扑和感知信息的信任因子,以研究影响和塑造。本章以影响和塑造之间的区别为基础。首先,这种区别很重要,因为它意味着影响是塑造的充分条件。其次,在计算社会科学中,促进对所研究的社会心理现象不模糊的模型的创建是很重要的。第三,这种区别很重要,因为它澄清了影响和塑造在不同的时间尺度上起作用——影响在短期内有效,而塑造在长期内更有效。
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Computational Red Teaming for Trusted Autonomous Systems
This chapter presents a model for influencing and shaping that employs computational red teaming. The model is demonstrated and validated computationally using a simulation environment where social influencing and shaping are applied to an artificial society. Network topology for situation awareness and a trust factor on perceived information were added to the classic Boids model to enable the investigation of influence and shaping. The chapter builds on the difference between influence and shaping. First, this distinction is important because it implies that influencing is a sufficient condition for shaping. Second, it is important in computational social sciences to facilitate the creation of models that are not ambiguous about the socio‐psychological phenomena under investigation. Third, the distinction is important because it clarifies that influencing and shaping work on different time scales – influencing is effective in the short term, whereas shaping is more effective in the long term.
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