Abstract
Metareasoning is reasoning about reasoning, or deciding how to decide. Employing metareasoning allows one to defer design decisions (such as algorithm selection) to runtime, so that a robot or autonomous system can adapt its reasoning process to failures or changes in the environment or system state. In addition, by monitoring and controlling its reasoning process, the system can more efficiently use its limited computational resources. This talk will describe metareasoning and the process of developing a metareasoning policy. It will also discuss two metareasoning approaches that we have developed. In the first, metareasoning is implemented as part of a ground robot autonomy stack. The metareasoning approach gives the robot the ability to recover from path planning failures, which leads to better mission performance. In the second, a multi-agent team uses metareasoning to select collaboration algorithms in response to changes in communication availability, which reduces the time needed to perform collaborative search missions. Finally, this talk will discuss future plans for metareasoning research and engineering.
Presenter Bio
Jeffrey W. Herrmann is the St. Abbo of Fleury Chair in Engineering and a professor in the Department of Mechanical Engineering at the Catholic University of America. He is a member of Society of Catholic Scientists, IISE, ASME, and the Design Society. Dr. Herrmann earned his B.S. in applied mathematics from Georgia Institute of Technology and received his Ph.D. in industrial and systems engineering from the University of Florida. Previously he was a professor at the University of Maryland. Dr. Herrmann received the Society of Manufacturing Engineers Jiri Tlusty Outstanding Young Manufacturing Engineer Award and was selected as a Diplomate of the Society for Health Systems. In 2016, his textbook, Engineering Decision Making and Risk Management, won the IIE/Joint Publishers Book of the Year award. He is an associate editor for the ASME Journal of Autonomous Vehicles and Systems.
Publication Date
9-15-2023
Document Type
Presentation
Recommended Citation
Herrmann, Jeffrey, "Metareasoning for Autonomous Systems: Improving Path Planning and Multiagent Collaboration" (2023). Seminars. 421.
https://scholars.unh.edu/ccom_seminars/421