CAREER: A Holistic Framework for the Analysis of Information Dynamics in Human Networks

由于认知限制、偏见和目标不一致，人类之间的通信与机器之间的通信不同，但人类行为在统计意义上仍然是可预测的。受此观察的启发，本项目研究了有关人类通信网络的理论和实践意义的问题。典型的场景包括人机系统和社交网络，其中自私的代理人，其中一些人倾向于偏见和限制，控制节点管理信息流，以最大限度地提高自己的感知回报。虽然相关模型已经在行为经济学领域进行了研究，但它们对现实通信和控制设置的扩展带来了许多开放性问题。 该项目将采用整体方法，从信息，控制和博弈论的角度联合考虑端到端的问题，利用所有三个学科的工具和模型。一个显着的应用程序开发的框架是在建模舆论两极分化和传播在社交网络的错误信息。另一应用涉及减轻信息处理系统中的偏差的影响。这项工作将解决有关新兴的人类通信模式的基本问题。这个不断发展的研究领域需要重新审视经典通信和控制理论的关键成果，并提出了重大挑战，需要多学科的方法和工具。研究成果预计将构成理解博弈论和经济学与信息论，控制，通信和压缩的相互作用的重要一步。 该项目的具体目标分为三组。第一组目标研究了目标不一致、认知局限和偏见的代理之间的沟通和压缩问题。第二组目标涉及意见演化的行为线性平均模型及其在极化动力学中的应用。最后一组目标是探索行为偏差信息网络中的真实数据收集策略。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Communications between humans is different from communications between machines due to cognitive limitations, biases, and misaligned objectives, yet human behavior is still predictable in a statistical sense. Motivated by this observation, this project investigates problems of theoretical and practical significance concerning human communication networks. Typical scenarios include human-machine systems and social networks where selfish agents, some of whom are prone to bias and limitations, control nodes to manage information flow to maximize their own perceived payoff. While relevant models have been studied in the field of Behavioral Economics, their extensions to realistic communication and control settings pose many open problems. This project will adopt a holistic approach that considers an end-to-end problem jointly from information, control, and game-theoretic perspectives, leveraging tools and models from all three disciplines. A notable application of the developed framework is on modeling public opinion polarization and misinformation spread over social networks. Another application pertains to mitigating the impact of bias in information processing systems. The work will address fundamental questions regarding the emerging human communication paradigm. This growing research field requires revisiting key results in classical communication and control theories and poses significant challenges, requiring approaches and tools from multiple disciplines. The research outcomes are expected to constitute an essential step in understanding the interplay of game theory and economics with information theory, control, communications, and compression. Specific goals of this project are categorized into three groups. The first set of goals investigates communication and compression problems between agents with misaligned objectives, cognitive limitations, and biases. The second set of goals concerns behavioral linear averaging models of opinion evolution and their applications in polarization dynamics. The final set of goals explores truthful data gathering strategies in behaviorally biased information networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.