APPLICATIONS OF QUANTUM PROBABILITY THEORY TO HUMAN-MACHINE COMMUNICATION NETWORKS
Abstract
Human reasoning and decision making in large networks is inevitably influenced by asynchronous, partially observable, and sequential communications. These facts drive the need for new probability and decision theories built “ground up” from non-commutative axiomatic foundations. For the past six years, based on previous AFOSR funding, we have been developing applications of one type of non-commutative probability theory, which is quantum probability theory. Now our goal is to develop applications quantum probability theory to human-machine communication networks. More specifically, we plan to accomplish the following two objectives: (A) Develop and test quantum probability theory for human communication networks. Our previous theoretical developments for dynamic and strategic decisions will be generalized and extended for application to human communication through networks. We will experimentally test the new theory with data collected in other research using human teams communicating sequentially through networks to make decisions. We will also compare the predictive accuracies of the new theories to traditional theories. This theory and research will be aimed to investigate small human network communications like chains of command. (B) Apply and test theories with dynamic information flows in larger networks. The theories developed in Goal A will be applied to larger networks and used to investigate dynamic network flows within a group of interacting human and artificial agents. The theory will be developed to account for possible measurement disturbance effects and non-commutative events occurring between information and actions in group decisions. Our ultimate goal is to predict, optimize, and control human-machine team networks for field tasks with limited time and resource.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2021
- Source ID
- FA95502010027
Entities
People
- Jerome Busemeyer
Organizations
- Air Force Office of Scientific Research
- Indiana University
- United States Air Force