Human Systems and Stories Lab (HSS)

Human interaction forms some of the most dynamic and intriguing examples of complex systems.

  • Current Interests
    • Models of Narrative Structure
      • Narrative Flow - the graph network relationship between story entities and the scenes in which they appear
      • Causation - how one scene leads to another, creating a causal chain of events
      • Scene Segmentation - accurately breaking a narrative into its scenes
      • PAPERS:
        • “Plot Extraction and the Visualization of Narrative Flow” (published @ Natural Language Engineering)
    • Social Influence, Misinformation, and Disinformation
      • Opinion Dynamics - how one person’s ideas and opinions change another’s through social interaction
      • Opinion Control - learn how opinions in a network can be driven to desired values and how to detect and prevent malicious use
      • Meme Mutation - how to memes mutate as they spread, and how does ones opinions influence that mutation and spread
      • PAPERS:
        • “Automatic Control of Opinion Dynamics in Social Networks” (accepted @ CCTA 2023)
        • “A Study of Three Influencer Archetypes for the Control of Opinion Spread in Time-varying Social Networks” (submitted to CDC 2023)
        • “Development of a Mutable Meme Model in the Context of a Contagion Spread Simulation” (accepted @ CCTA 2023)
    • Discourse and Conversation
      • Conversation and Discussion Analysis - extract important metrics from discussions that reveal how that conversation went and was received
      • Conversation Modeling - what makes a good conversation and how could we extract and model it mathematically
      • PAPERS:
        • “A Toolbox for Understanding the Dynamics of Small Group Discussions” (in review @ The International Journal of Artificial Intelligence in Education)
  • Former Interests
    • Government
      • Fair Election - how can we make elections more fair and accessible without compromising security
      • Legal Systems - tools to aid in legal analysis, court proceedings, and law enforcement
      • International Relations - modeling the relationships between governing bodies and those who reside in them
      • PAPERS:
        • “Forecasting Political Instability: Control-theoretic Modeling of International Conflict” (BYU Undergraduate Thesis)
    • Multi-Agent Systems and Game Theory
      • Cooperation and Competition - analysis of agent based cooperation and competition models
      • Coalition Robustness of Multiagent Systems
      • PAPERS:
        • “Stability Robustness Conditions for Gradient Play Differential Games with Partial Participation in Coalitions”
        • “Coalition Robustness of Multiagent Systems”
        • “Stability Robustness Conditions for Market Power Analysis in Industrial Organization Networks”
        • “Cooperation-based Clustering for Profit-Maximizing Organizational Design”

This lab explores the way information is processed by these systems and seeks to define better modes of interaction to achieve various purposes. By focusing on decision processes in these inherently multi-agent systems, a number of abstract concepts such as competition, cooperation, persuasion, and deception can be rigorously analyzed.


Coalition Robustness of Multiagent Systems

This research explores the interplay of cooperation and competition in multiagent dynamics. Our study begins with the stability robustness of multiagent systems with respect to uncertain coalition structure. Such systems arise naturally from a variety of compartmental models, including those used in security analysis, economics, ecology, etc. Moreover, coalition robustness becomes significant when conducting organizational analysis, such as in merger simulation, market structure analysis, or in other areas of industrial organization.

Forecasting Political Instability

Creating and analyzing models of international political conflict is a valuable problem because understanding the dynamics of such systems can be an invaluable aid to appropriately interpret political behavior. The challenge is to create a tractable method that retains political meaning and preserves enough information of the underlying dynamic system so as to support the development of predictive models. This project is building a control-theoretic model for the Israeli-Palestinian conflict that is amenable to optimization and expresses the tradeoff between internal and external coalition strength.