Finally, “The Perceptual Belief Problem: Why Explainability Is a Tough Challenge in Social Robotics,” by Thellman and Ziemke, identifies the challenge to facilitate the attribution of appro- priate intentional states, such as beliefs and desires, to robots as one fundamental mechanism in people's ability to explain and ...
Jul 11, 2021 · The explainability of robotic systems depends on people's ability to reliably attribute perceptual beliefs to robots.
The explainability of robotic systems depends on people's ability to reliably attribute perceptual beliefs to robots.
Aug 25, 2021 · The explainability of robotic systems depends on people's ability to reliably attribute perceptual beliefs to robots, i.e., what robots know (or ...
The perceptual belief problem focuses on helping humans determine what a robot believes or knows about the environment it shares with other agents-both human ...
Résumé: The explainability of robotic systems depends on people's ability to reliably attribute perceptual beliefs to robots, i.e., what robots know (or ...
Oct 23, 2020 · In a series of experiments, we set out to investigate people's ability to keep track of what robots know or believe about objects and events in the environment.
Aug 30, 2021 · This thesis addresses the scope and limits of people's ability to interact socially with robots by treating them as intentional agents.
The perceptual belief problem: Why explainability is a tough challenge in social robotics. S Thellman, T Ziemke. ACM Transactions on Human-Robot Interaction ...
In this article, we explain why this is a significant, difficult, and unique problem in social robotics. The inability to judge what a robot knows (and does not ...