Meaningless Statements in Performance Measurement for Intelligent Machines

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 study of robots and other intelligent machines, we will give a variety of examples of meaningless and meaningful statements. We 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 vs. moving, and of determining if one unmanned vehicle’s route is shorter than another’s.

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When: May 7, 2020 03:30 PM Eastern Time (US and Canada)

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