基于意识的推荐:被动互动学习系统

T. Yamaguchi, T. Nishimura, K. Takadama
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引用次数: 1

摘要

在人工智能和机器人技术中,人机界面的设计是一个重要的问题。有两个问题,一个是以机器为中心的交互设计,使人类适应操作机器人或系统。另一个是以人为中心的交互设计,使其适应人类。本研究针对后一个问题。本文提出了一种交互式学习系统,以帮助人类向真实偏好积极改变偏好,然后讨论了感知效应的评价。该系统通过可视化人类行为的痕迹来被动地反映人类的智力。实验结果表明,被试被分为重度使用者和轻度使用者两组,在相同的视觉化条件下,他们之间的效果是不同的。他们还表明,作者的系统提高了重度用户和轻度用户决定最喜欢的计划的效率。关键词适应性,意识,重用户,人机界面,交互学习,轻用户,偏好,推荐,强化学习
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Awareness Based Recommendation: Passively Interactive Learning System
In Artificial Intelligence and Robotics, one of the important issues is to design Human interface. There are two issues, one is the machine-centered interaction design to adapt humans for operating the robots or systems. Another one is the human-centered interaction design to make it adaptable for humans. This research aims at latter issue. This paper presents the interactive learning system to assist positive change in the preference of a human toward the true preference, then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors’ system improves the efficiency for deciding the most preferred plan for both heavy users and light users. KeywoRdS Adaptable, Awareness, Heavy User, Human Interface, Interactive Learning, Light User, Preference, Recommendation, Reinforcement Learning
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