System-Scientific Methods

Linan Huang, Quanyan Zhu

Research output: Chapter in Book/Report/Conference proceedingChapter


In Chap. 2, we briefly introduce essential system-scientific tools for modeling, analyzing, and mitigating cognitive vulnerabilities and cognitive attacks. Decision theory in Sect. 2.1 provides a scientific foundation of making decisions for single agents with different rationality levels under stochastic environments. Game theory is introduced in Sect. 2.2 to model the strategic interactions among multiple agents under several basic game settings and their associated Nash Equilibrium (NE) solution concepts. To address the challenges of incomplete information in decision-making and game modeling, we present two learning schemes in Sect. 2.3. These tools provide a system-scientific perspective to evaluate and reduce uncertainty in HCPSs, as illustrated by the blue and red lines in Fig. 2.1, respectively. We refer the readers to the notes at the end of each section for recent advances and relevant references.

Original languageEnglish (US)
Title of host publicationSpringerBriefs in Computer Science
Number of pages13
StatePublished - 2023

Publication series

NameSpringerBriefs in Computer Science
VolumePart F267
ISSN (Print)2191-5768
ISSN (Electronic)2191-5776


  • Bayesian learning
  • Cumulative prospect theory
  • Expected utility theory
  • Game theory
  • Nash equilibrium
  • Reinforcement learning
  • Von Neumann–Morgenstern utility theorem

ASJC Scopus subject areas

  • General Computer Science


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