Proceedings of the 7th International Conference on Human-Agent Interaction最新文献_第3页

Effect of an Educational Support Robot Displaying Utterance Contents on a Learning System 教育支持机器人话语内容显示对学习系统的影响

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3352782

Shunsuke Shibata, Felix Jimenez, K. Murakami

引用次数: 1

Analyzing Eye Movements in Interview Communication with Virtual Reality Agents 基于虚拟现实代理的访谈交流眼动分析

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3351889

Fuhui Tian, S. Okada, K. Nitta

引用次数: 5

Towards Digitally-Mediated Sign Language Communication 迈向数字媒介的手语交流

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3352794

Kalin Stefanov, M. Bono

引用次数: 2

Hierarchical Affordance Discovery using Intrinsic Motivation 基于内在动机的分层功能发现

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3351898

A. Manoury, S. Nguyen, Cédric Buche

{"title":"Hierarchical Affordance Discovery using Intrinsic Motivation","authors":"A. Manoury, S. Nguyen, Cédric Buche","doi":"10.1145/3349537.3351898","DOIUrl":"https://doi.org/10.1145/3349537.3351898","url":null,"abstract":"To be capable of life-long learning in a real-life environment, robots have to tackle multiple challenges. Being able to relate physical properties they may observe in their environment to possible interactions they may have is one of them. This skill, named affordance learning, is strongly related to embodiment and is mastered through each person's development: each individual learns affordances differently through their own interactions with their surroundings. Current methods for affordance learning usually use either fixed actions to learn these affordances or focus on static setups involving a robotic arm to be operated. In this article, we propose an algorithm using intrinsic motivation to guide the learning of affordances for a mobile robot. This algorithm is capable to autonomously discover, learn and adapt interrelated affordances without pre-programmed actions. Once learned, these affordances may be used by the algorithm to plan sequences of actions in order to perform tasks of various difficulties. We then present one experiment and analyse our system before comparing it with other approaches from reinforcement learning and affordance learning.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130902691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Effects of Turn-Taking Dynamics Without Contingency: A Visual Interaction Experiment 无偶然性的轮转动力学效应:一个视觉交互实验

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3352778

Ryohei Irie, Takeshi Konno

引用次数: 0

Calibrate My Smile: Robot Learning Its Facial Expressions through Interactive Play with Humans 校准我的微笑:机器人通过与人类互动学习面部表情

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3351890

Dino Ilic, Ivana Žužić, D. Brscic

引用次数: 3

Pocketable-Bones: A Portable Robot Sharing Interests with User in the Breast Pocket 口袋骨:一种与用户在胸前口袋分享兴趣的便携式机器人

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3352768

Ryosuke Mayumi, Naoki Ohshima, M. Okada

引用次数: 1

A Markovian Method for Predicting Trust Behavior in Human-Agent Interaction 人- agent交互信任行为预测的马尔可夫方法

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3351905

D. Pynadath, Ning Wang, Sreekar Kamireddy

{"title":"A Markovian Method for Predicting Trust Behavior in Human-Agent Interaction","authors":"D. Pynadath, Ning Wang, Sreekar Kamireddy","doi":"10.1145/3349537.3351905","DOIUrl":"https://doi.org/10.1145/3349537.3351905","url":null,"abstract":"Trust calibration is critical to the success of human-agent interaction (HAI). However, individual differences are ubiquitous in people's trust relationships with autonomous systems. To assist its heterogeneous human teammates calibrate their trust in it, an agent must first dynamically model them as individuals, rather than communicating with them all in the same manner. It can then generate expectations of its teammates' behavior and optimize its own communication based on the current state of the trust relationship it has with them. In this work, we examine how an agent can generate accurate expectations given observations of only the teammate's trust-related behaviors (e.g., did the person follow or ignore its advice?). In addition to this limited input, we also seek a specific output: accurately predicting its human teammate's future trust behavior (e.g., will the person follow or ignore my next suggestion?). In this investigation, we construct a model capable of generating such expectations using data gathered in a human-subject study of behavior in a simulated human-robot interaction (HRI) scenario. We first analyze the ability of measures from a pre-survey on trust-related traits to accurately predict subsequent trust behaviors. However, as the interaction progresses, this effect is dwarfed by the direct experience. We therefore analyze the ability of sequences of prior behavior by the teammate to accurately predict subsequent trust behaviors. Such behavioral sequences have shown to be indicative of the subjective beliefs of other teammates, and we show here that they have a predictive power as well.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130097004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

A Model of Social Explanations for a Conversational Movie Recommendation System 会话式电影推荐系统的社会解释模型

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3351899

Florian Pecune, Shruti Murali, Vivian Tsai, Yoichi Matsuyama, Justine Cassell

引用次数: 36

The Social Psychology of Human-agent Interaction 人-代理互动的社会心理学

Proceedings of the 7th International Conference on Human-Agent Interaction Pub Date : 2019-09-25 DOI: 10.1145/3349537.3351909

J. Gratch

{"title":"The Social Psychology of Human-agent Interaction","authors":"J. Gratch","doi":"10.1145/3349537.3351909","DOIUrl":"https://doi.org/10.1145/3349537.3351909","url":null,"abstract":"Designers of human-agent systems often assume that users interact with machines as if they are interacting with another person. As a consequences, fidelity to human behavior is often viewed as the gold standard for judging agent design, and theories of human social psychology are often accepted without question as a framework for informing human-agent interaction. This assumption was given strength by the pioneering work of Cliff Nass showing that many of the effects studied within social psychology seem to apply to human-machine interaction. In this talk, I will illustrate that these social effects are much weaker than widely supposed, and that the differences in how people treat machines are arguably more interesting than the similarities. These differences can lead to novel insights into human social cognition and unique technological solutions to intractable social problems. I will discuss this in the context of our research on education and mental health. Thus, rather copying human behavior, I will argue that HAI researchers should aim to transcend conventional forms of social interaction, and work towards novel theoretical frameworks that address the novel psychology of human-agent interaction.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121398772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3