In the game, a player wishes to estimate an unknown value on a sliding scale by asking a series of questions whose answer is binary (yes or no). In this way, scientists say, their research findings could lead to new techniques for machines to ask other machines questions, or for machines and humans to query each other.
ARL senior scientist Dr. Brian Sadler teamed with University of Michigan researchers Hye Won Chung, Lizhong Zheng, and Professor Alfred O. Hero to conduct the study, which appears in the February 2018 issue of the IEEE Transactions on Information Theory.
Work - Part - Study - Methods - Machines
The work is part of a larger study to develop methods for machines and humans to interact.
"It is well known that artificial intelligence systems, such as those found nowadays on every smartphone, can answer at least some questions," Sadler said. "They can even win a game like Jeopardy, focusing on only one question at the time. A real, purposeful conversation, especially in complicated military environments, is different. It requires the AI system to understand a whole sequence of questions and answers, and to handle every question or answer with consideration of what has been asked or answered before. Such computer algorithms do not yet exist, and the scientific theory for building such algorithms is not yet developed."
Sadler - Challenge - Ways - Machine
Sadler said it is a signifcant challenge to find ways for a machine to query a human that efficiently takes...
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