Additional Calendars
Calendar Views
Conferences and Meetings
Law School
Special Events

EAS PhD Proposal Defense Presentation by Christopher J. Hixenbaugh

When: Tuesday, December 14, 2021
2:00 PM - 3:00 PM
Where: Online
Description: EAS PhD Proposal Defense Presentation by Christopher J. Hixenbaugh

Date: December 14, 2021
Time: 2:00 p.m.

Topic: A Model-Free Deep Reinforcement Learning Approach to UUV Control with Mixed Numerical Precision

Zoom Teleconference:
For meeting access please contact Anne-Marie Bedard at

Control systems for Unmanned Undersea Vehicles (UUVs) are typically implemented using Proportional Integral Derivative (PID) control systems. PID control systems for UUVs are resource-intensive to tune because they require several engineers, marine operators, and ship crew to spend time offshore to tune the controller. Furthermore, PID controllers rely on complex dynamic system models that contain assumptions to reduce the computational complexity of the models but degrade the controller's performance if an environmental condition is encountered that conflicts with an assumption. In this study, a Deep Reinforcement Learning control system based on the Deep Deterministic Policy Gradient (DDPG) algorithm is studied for a UUV control system. The DDPG algorithm is model-free, meaning that a complex dynamic system model is not needed to learn and provide optimal control performance. Secondly, Deep Reinforcement Learning control systems are tuned autonomously, which can greatly reduce the resources needed for controller tuning. One drawback to Deep Reinforcement Learning is that it can be more computationally and resource-intensive than is acceptable for some situations. To improve upon this, this study will investigate how mixed floating-point precision with loss scaling can be used to reduce the time and computational resources needed to train the DDPG agent.

ADVISOR(S): Dr. Alfa Heryudono, Department of Mathematics (, 508-999-8516)

Dr. Scott Field, Department of Mathematics
Dr. Firas Khatib, Department of Computer and Information Science
Dr. Ming Shao, Department of Computer and Information Science
Dr. Eugene Chabot, Naval Undersea Warfare Center Division Newport

NOTE: All EAS Students are ENCOURAGED to attend.
Contact: > See Description for contact information
Topical Areas: Alumni, Faculty, Staff and Administrators, Students, Students, Graduate, Students, Undergraduate, Mathematics, Bioengineering, Civil and Environmental Engineering, College of Engineering, Computer and Information Science, Co-op Program, Electrical and Computer Engineering, Mechanical Engineering, Physics