受用户活动和脱离影响的机器人接近行为的深度强化学习

IF 3.8 2区计算机科学 Q2 ROBOTICS

International Journal of Social Robotics Pub Date : 2023-09-07 DOI:10.1007/s12369-023-01044-7

Luca Raggioli, F. A. D'Asaro, Silvia Rossi

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Deep Reinforcement Learning for Robotic Approaching Behavior Influenced by User Activity and Disengagement

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Deep Reinforcement Learning for Robotic Approaching Behavior Influenced by User Activity and Disengagement

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来源期刊

International Journal of Social Robotics ROBOTICS-

CiteScore

9.80

自引率

8.50%

发文量

期刊介绍： Social Robotics is the study of robots that are able to interact and communicate among themselves, with humans, and with the environment, within the social and cultural structure attached to its role. The journal covers a broad spectrum of topics related to the latest technologies, new research results and developments in the area of social robotics on all levels, from developments in core enabling technologies to system integration, aesthetic design, applications and social implications. It provides a platform for like-minded researchers to present their findings and latest developments in social robotics, covering relevant advances in engineering, computing, arts and social sciences. The journal publishes original, peer reviewed articles and contributions on innovative ideas and concepts, new discoveries and improvements, as well as novel applications, by leading researchers and developers regarding the latest fundamental advances in the core technologies that form the backbone of social robotics, distinguished developmental projects in the area, as well as seminal works in aesthetic design, ethics and philosophy, studies on social impact and influence, pertaining to social robotics.