scholarly journals A Comparative Study on Artificial Cognition and Advances in Artificial Intelligence for Social-Human Robot Interaction

2018 ◽  
Vol 8 (1) ◽  
pp. 1-10
Author(s):  
Amitvikram Nawalagatti et al., Amitvikram Nawalagatti et al., ◽  
Keyword(s):  
Artificial Intelligence ◽  
Comparative Study ◽  
Human Robot Interaction ◽  
Robot Interaction

scholarly journals Reports on the 2014 AAAI Fall Symposium Series

AI Magazine ◽  
2015 ◽  
Vol 36 (3) ◽  
pp. 107-112
Author(s):  
Adam B. Cohen ◽  
Sonia Chernova ◽  
James Giordano ◽  
Frank Guerin ◽  
Kris Hauser ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Informatics ◽  
Autonomous Robots ◽  
Human Robot Interaction ◽  
Energy Market ◽  
Washington Dc ◽  
Robot Interaction ◽  
Language Access ◽  
Symposium Series ◽  
And Behavior

The AAAI 2014 Fall Symposium Series was held Thursday through Saturday, November 13–15, at the Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC. The titles of the seven symposia were Artificial Intelligence for Human-Robot Interaction, Energy Market Prediction, Expanding the Boundaries of Health Informatics Using AI, Knowledge, Skill, and Behavior Transfer in Autonomous Robots, Modeling Changing Perspectives: Reconceptualizing Sensorimotor Experiences, Natural Language Access to Big Data, and The Nature of Humans and Machines: A Multidisciplinary Discourse. The highlights of each symposium are presented in this report.

scholarly journals Reports of the AAAI 2016 Spring Symposium Series

AI Magazine ◽  
2017 ◽  
Vol 37 (4) ◽  
pp. 83-88
Author(s):  
Christopher Amato ◽  
Ofra Amir ◽  
Joanna Bryson ◽  
Barbara Grosz ◽  
Bipin Indurkhya ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Observational Studies ◽  
Human Error ◽  
Well Being ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Symposium Series ◽  
Research Platform ◽  
Challenges And Opportunities

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2016 Spring Symposium Series on Monday through Wednesday, March 21-23, 2016 at Stanford University. The titles of the seven symposia were (1) AI and the Mitigation of Human Error: Anomalies, Team Metrics and Thermodynamics; (2) Challenges and Opportunities in Multiagent Learning for the Real World (3) Enabling Computing Research in Socially Intelligent Human-Robot Interaction: A Community-Driven Modular Research Platform; (4) Ethical and Moral Considerations in Non-Human Agents; (5) Intelligent Systems for Supporting Distributed Human Teamwork; (6) Observational Studies through Social Media and Other Human-Generated Content, and (7) Well-Being Computing: AI Meets Health and Happiness Science.

scholarly journals Special Issue in Artificial Intelligence

2019 ◽  
Vol 30 (1) ◽  
pp. 7-8
Author(s):  
Dora Maria Ballesteros
Keyword(s):  
Artificial Intelligence ◽  
Communication Networks ◽  
Language Processing ◽  
Autonomous Systems ◽  
Big Data Analytics ◽  
Human Robot Interaction ◽  
Support Vector ◽  
Special Issue ◽  
Science And Engineering ◽  
Robot Interaction

Artificial intelligence (AI) is an interdisciplinary subject in science and engineering that makes it possible for machines to learn from data. Artificial Intelligence applications include prediction, recommendation, classification and recognition, object detection, natural language processing, autonomous systems, among others. The topics of the articles in this special issue include deep learning applied to medicine [1, 3], support vector machine applied to ecosystems [2], human-robot interaction [4], clustering in the identification of anomalous patterns in communication networks [5], expert systems for the simulation of natural disaster scenarios [6], real-time algorithms of artificial intelligence [7] and big data analytics for natural disasters [8].

scholarly journals Four-Features Evaluation of Text to Speech Systems for Three Social Robots

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 267
Author(s):  
Fernando Alonso Martin ◽  
María Malfaz ◽  
Álvaro Castro-González ◽  
José Carlos Castillo ◽  
Miguel Ángel Salichs
Keyword(s):  
Comparative Study ◽  
Communication Skills ◽  
Social Robotics ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Text To Speech ◽  
Robot Interaction ◽  
Speech Synthesizer ◽  
Human Voice ◽  
Research Questions

The success of social robotics is directly linked to their ability of interacting with people. Humans possess verbal and non-verbal communication skills, and, therefore, both are essential for social robots to get a natural human–robot interaction. This work focuses on the first of them since the majority of social robots implement an interaction system endowed with verbal capacities. In order to do this implementation, we must equip social robots with an artificial voice system. In robotics, a Text to Speech (TTS) system is the most common speech synthesizer technique. The performance of a speech synthesizer is mainly evaluated by its similarity to the human voice in relation to its intelligibility and expressiveness. In this paper, we present a comparative study of eight off-the-shelf TTS systems used in social robots. In order to carry out the study, 125 participants evaluated the performance of the following TTS systems: Google, Microsoft, Ivona, Loquendo, Espeak, Pico, AT&T, and Nuance. The evaluation was performed after observing videos where a social robot communicates verbally using one TTS system. The participants completed a questionnaire to rate each TTS system in relation to four features: intelligibility, expressiveness, artificiality, and suitability. In this study, four research questions were posed to determine whether it is possible to present a ranking of TTS systems in relation to each evaluated feature, or, on the contrary, there are no significant differences between them. Our study shows that participants found differences between the TTS systems evaluated in terms of intelligibility, expressiveness, and artificiality. The experiments also indicated that there was a relationship between the physical appearance of the robots (embodiment) and the suitability of TTS systems.

Of Mental States and Machine Learning

2016 ◽  
Vol 60 (1) ◽  
pp. 1362-1366 ◽  
Author(s):  
Andrew Best ◽  
Samantha F. Warta ◽  
Katelynn A. Kapalo ◽  
Stephen M. Fiore
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Social Cognition ◽  
Mental State ◽  
Response Times ◽  
Interdisciplinary Approach ◽  
Mental States ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Machine Learning Classifiers

Using research in social cognition as a foundation, we studied rapid versus reflective mental state attributions and the degree to which machine learning classifiers can be trained to make such judgments. We observed differences in response times between conditions, but did not find significant differences in the accuracy of mental state attributions. We additionally demonstrate how to train machine classifiers to identify mental states. We discuss advantages of using an interdisciplinary approach to understand and improve human-robot interaction and to further the development of social cognition in artificial intelligence.

The Race Between Cognitive and Artificial Intelligence

2020 ◽  
Vol 16 (1) ◽  
pp. 1-16
Author(s):  
Anshu Saxena Arora ◽  
Amit Arora
Keyword(s):  
Artificial Intelligence ◽  
Social Cognitive ◽  
Code Of Ethics ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Cognitive Intelligence ◽  
Verbal Language ◽  
Ethical Implications ◽  
Research Fields ◽  
Human Ability

Research on human-robot interaction (HRI) is growing; however, focus on the congruent socio-behavioral HRI research fields of social cognition, socio-behavioral intentions, and code of ethics is lacking. Humans possess an inherent ability of integrating perception, cognition, and action; while robots may have limitations as they may not recognize an object or a being, navigate a terrain, and/or comprehend written or verbal language and instructions. This HRI research focuses on issues and challenges for both humans and robots from social, behavioral, technical, and ethical perspectives. The human ability to anthropomorphize robots and adoption of ‘intentional mindset' toward robots through xenocentrism have added new dimensions to HRI. Robotic anthropomorphism plays a significant role in how humans can be successful companions of robots. This research explores social cognitive intelligence versus artificial intelligence with a focus on privacy protections and ethical implications of HRI while designing robots that are ethical, cognitively and artificially intelligent, and social human-like agents.

scholarly journals Personalization and Localization in Human-Robot Interaction: A Review of Technical Methods

Robotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 120
Author(s):  
Mehdi Hellou ◽  
Norina Gasteiger ◽  
Jong Yoon Lim ◽  
Minsu Jang ◽  
Ho Seok Ahn
Keyword(s):  
Artificial Intelligence ◽  
Current Literature ◽  
State Of The Art ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Social Conventions ◽  
Verbal Skills ◽  
Education Industry ◽  
The Social

Personalization and localization are important when developing social robots for different sectors, including education, industry, healthcare or restaurants. This allows for an adjustment of robot behaviors according to the needs, preferences or personality of an individual when referring to personalization or to the social conventions or the culture of a country when referring to localization. However, there are different models that enable personalization and localization presented in the current literature, each with their advantages and drawbacks. This work aims to help researchers in the field of social robotics by reviewing and analyzing different papers in this domain. We specifically focus our review by exploring different robots that employ distinct models for the adaptation of the robot to its environment. Additionally, we study an array of methods used to adapt the nonverbal and verbal skills of social robots, including state-of-the-art techniques in artificial intelligence.

Sign in / Sign up

Export Citation Format

Share Document