Paper ID | SPTM-13.5 | ||
Paper Title | Cognitive Memory Constrained Human Decision Making based on Multi-source Information | ||
Authors | Baocheng Geng, Chen Quan, Pramod Varshney, Syracuse University, United States | ||
Session | SPTM-13: Models, Methods and Algorithms 1 | ||
Location | Gather.Town | ||
Session Time: | Thursday, 10 June, 13:00 - 13:45 | ||
Presentation Time: | Thursday, 10 June, 13:00 - 13:45 | ||
Presentation | Poster | ||
Topic | Signal Processing Theory and Methods: [SSP] Statistical Signal Processing | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | Unlike decision making systems made up of physical sensors where the system parameters are known a priori and can be controlled at will, human behavior in decision making is complex and uncertain. The objective of this work is to study how humans make decisions based on internal and external sources of information under cognitive memory limitations. Due to constrained capacity of working memory, humans are known to perform cognitive tasks and update their beliefs in a sequential manner rather than in parallel. In a Bayesian hypothesis testing framework, we derive the metrics for performance evaluation and comparison when the humans use different ordering of information for processing and to update their beliefs. We show that an appropriate order of information sources can help a cognitive memory limited human make better decisions. Simulations are presented to corroborate the theoretical results. |