This project develops a Queuing Network (QN) architecture and modeling methodology for analyzing the Mind-Body System (MBS). The QN-MBS provides the mathematical and computational structure of the modeling framework, which will incorporate and integrate some other related modeling methods such as control theory, biomechanics, optimization, machine learning, motor control, and cognitive and neural science. Through several decades of prior research, the researchers of this project have developed a Queuing Network Cognitive Architecture for modeling the human mind and several models of human movement and body activities with control theory and biomechanics. These prior works both lay the foundation and need significant integration and developments for modeling the integrated Mind-Body System. To address this challenge is the goal and scope of this project.
People
Yili
Liu
IOE
Engineering
Bernard
Martin
IOE
Engineering
Funding
Funding: $30K (2022)
Goal: The specific desired outcome of this project is to develop a Queuing Network (QN) architecture and modeling methodology for analyzing the Mind-Body System (MBS), which incorporates and integrates some other related modeling approaches and methods such as motor control, biomechanics, cognitive and neural science.
Token Investors: Yili Liu, Bernard Martin
Project ID: 1024