Dr. Fred S. Roberts will present a talk titled “Meaningless Statements about Performance of Intelligent Machines in Emergency Management” at 10 a.m. Monday, Nov. 16, via Zoom.
Roberts is a distinguished professor of mathematics at Rutgers University and director of the Command, Control and Interoperability Center for Advanced Data Analysis, founded as a University Center of Excellence of the Department of Homeland Security. He is emeritus director of DIMACS, one of the original National Science Foundation science and technology centers, with 14 academic and industrial partners and approximately 350 affiliated scientists.
Among his current research interests are resilience of supply chains, challenges of disasters and pandemics, stadium and large-venue security, resource allocation, maritime cybersecurity, and the homeland security aspects of global environmental change. Roberts has authored four books, edited 24 additional books, and authored 200 scientific articles, some translated into Russian and Chinese, including the first book on maritime cybersecurity in 2017 and a 2019 book titled Mathematics of Planet Earth.
Among his awards are the Commemorative Medal of the Union of Czech Mathematicians and Physicists, the Distinguished Service Award of the Association of Computing Machinery Special Interest Group on Algorithms and Computation Theory, Fellow of the American Mathematical Society, the National Science Foundation Science and Technology Centers Pioneer Award, and an honorary doctorate from the University of Paris-Dauphine.
Abstract: A statement involving scales of measurement is called meaningless if its truth or falsity can depend on the particular versions of scales that are used in the statement. Using examples from the use of robots, drones, unmanned land vehicles and other intelligent machines in emergency management, we will give a variety of examples of meaningless and meaningful statements. He will briefly discuss the mathematical foundations of the theory of meaningfulness, discuss ways to average scores that lead to meaningful statements, and discuss meaningful and meaningless statements involving shortest paths and other concepts in combinatorial optimization. Applications will include meaningfulness of comparing machine performance on different tasks, of comparing average robot performance on lifting versus moving, and of determining if one unmanned vehicle’s route is shorter than another’s.