2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)最新文献_第5页

Analysis of How Personality Traits Affect Children's Conversational Play with an Utterance-Output Device 用话语-输出装置分析人格特质对儿童会话游戏的影响

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-08-01 DOI: 10.1109/DEVLRN.2019.8850700

Jun Ichikawa, Kazuhiro Mitsukuni, Yukari Hori, Y. Ikeno, Leblanc Alexandre, T. Kawamoto, Yukiko Nishizaki, N. Oka

{"title":"Analysis of How Personality Traits Affect Children's Conversational Play with an Utterance-Output Device","authors":"Jun Ichikawa, Kazuhiro Mitsukuni, Yukari Hori, Y. Ikeno, Leblanc Alexandre, T. Kawamoto, Yukiko Nishizaki, N. Oka","doi":"10.1109/DEVLRN.2019.8850700","DOIUrl":"https://doi.org/10.1109/DEVLRN.2019.8850700","url":null,"abstract":"Smart speakers (such as Amazon Echo and Google Home) are becoming a popular addition to homes, and it is expected that they will be used as parental support in the future. Previous studies have analyzed the history logs of the uses of their services and gathered impressions of them using questionnaire surveys and qualitative interviews. Details of how children interact with smart speakers have not been fully investigated. This study investigated children's interactions with an utterance-output device, such as a smart speaker, and focuses on the influences of the children's personality traits. The experiment was conducted in a realistic setting. The results indicate that the less nervous, more emotionally stable, or more adaptable to communication different from that at home children are, the more closely they engage in conversational play with an utterance-output device. The findings suggest that effective conversational play, which can lessen anxiety toward a novel utterance-output device, will be required in future interaction design.","PeriodicalId":318973,"journal":{"name":"2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121394591","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: 2

How development in the Bayesian brain facilitates learning 贝叶斯大脑的发育是如何促进学习的

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-08-01 DOI: 10.1109/DEVLRN.2019.8850720

D. Oliva, A. Philippsen, Y. Nagai

{"title":"How development in the Bayesian brain facilitates learning","authors":"D. Oliva, A. Philippsen, Y. Nagai","doi":"10.1109/DEVLRN.2019.8850720","DOIUrl":"https://doi.org/10.1109/DEVLRN.2019.8850720","url":null,"abstract":"The Bayesian brain model has been proposed as a possible simplified view of the inner workings of the human brain. According to this view, the brain is a prediction machine with an internal model of the world which can be improved by comparing the generated predictions to sensory observations. Knowledge about expected events (prior predictions) are combined with observations (sensory input) into posterior beliefs, helping us to infer what is happening in the environment. While it is commonly acknowledged that this integration is optimally performed in a Bayesian way, the effects of Bayesian inference on the developmental process are less well investigated. In this study, we propose a computational framework which combines Bayesian inference with recurrent neural network training. We demonstrate that learning in this framework proceeds in a human-like manner in that the system is able to appropriately weight sensory input and prior predictions depending on their reliability which increases during development. As a result, during the course of learning, the model gradually switches from relying on sensory information to a stronger reliance on own predictions and becomes more robust against disturbances in the environment.","PeriodicalId":318973,"journal":{"name":"2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129395736","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: 6

Mindreading for Robots: Predicting Intentions via Dynamical Clustering of Human Postures 机器人读心术:通过人类姿势的动态聚类预测意图

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-08-01 DOI: 10.1109/DEVLRN.2019.8850698

Samuele Vinanzi, C. Goerick, A. Cangelosi

{"title":"Mindreading for Robots: Predicting Intentions via Dynamical Clustering of Human Postures","authors":"Samuele Vinanzi, C. Goerick, A. Cangelosi","doi":"10.1109/DEVLRN.2019.8850698","DOIUrl":"https://doi.org/10.1109/DEVLRN.2019.8850698","url":null,"abstract":"Recent advancements in robotics suggest a future where social robots will be deeply integrated in our society. In order to understand humans and engage in finer interactions, robots would greatly benefit from the ability of intention reading: the capacity to discern the high-level goal that is driving the low-level actions of an observed agent. This is particularly useful in joint action scenarios, where human and robot must collaborate to reach a shared goal: if the latter can predict the actions of the former, it will be able to use this information for decision making in order to improve the quality of the cooperation. This research proposes a novel artificial cognitive architecture, based on the developmental robotics paradigm, that can estimate the goals of a human partner engaged in a joint task to modulate synergistic behavior. This is accomplished using unsupervised dynamical clustering of human skeletal data and a hidden semi-Markov chain. The effectiveness of this architecture has been tested through an interactive cooperative experiment involving a block building game, the iCub robot and a human. The results show that the former is able to adopt a collaborative behavior by performing intention reading based on the partner's physical clues.","PeriodicalId":318973,"journal":{"name":"2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126313353","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: 9

Hierarchical Control for Bipedal Locomotion using Central Pattern Generators and Neural Networks 基于中枢模式发生器和神经网络的两足运动层次控制

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-08-01 DOI: 10.1109/DEVLRN.2019.8850683

S. Auddy, S. Magg, S. Wermter

{"title":"Hierarchical Control for Bipedal Locomotion using Central Pattern Generators and Neural Networks","authors":"S. Auddy, S. Magg, S. Wermter","doi":"10.1109/DEVLRN.2019.8850683","DOIUrl":"https://doi.org/10.1109/DEVLRN.2019.8850683","url":null,"abstract":"The complexity of bipedal locomotion may be attributed to the difficulty in synchronizing joint movements while at the same time achieving high-level objectives such as walking in a particular direction. Artificial central pattern generators (CPGs) can produce synchronized joint movements and have been used in the past for bipedal locomotion. However, most existing CPG-based approaches do not address the problem of high-level control explicitly. We propose a novel hierarchical control mechanism for bipedal locomotion where an optimized CPG network is used for joint control and a neural network acts as a high-level controller for modulating the CPG network. By separating motion generation from motion modulation, the high-level controller does not need to control individual joints directly but instead can develop to achieve a higher goal using a low-dimensional control signal. The feasibility of the hierarchical controller is demonstrated through simulation experiments using the Neuro-Inspired Companion (NICO) robot. Experimental results demonstrate the controller's ability to function even without the availability of an exact robot model.","PeriodicalId":318973,"journal":{"name":"2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"6 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129497822","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: 7

Modelling the Single Word to Multi-Word Transition Using Matrix Completion 基于矩阵补全的单字到多字转换建模

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-08-01 DOI: 10.1109/DEVLRN.2019.8850708

Gabriella Pizzuto, Timothy M. Hospedales, O. Capirci, A. Cangelosi

引用次数: 1

An interdisciplinary overview of developmental indices and behavioral measures of the minimal self 最小自我的发展指数和行为测量的跨学科概述

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-06-24 DOI: 10.1109/DEVLRN.2019.8850703

Yasmin Kim Georgie, G. Schillaci, V. Hafner

引用次数: 10

Contextual Relabelling of Detected Objects 检测对象的上下文重新标记

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-06-06 DOI: 10.1109/DEVLRN.2019.8850686

Faisal Alamri, N. Pugeault

引用次数: 6

Autonomous Reinforcement Learning of Multiple Interrelated Tasks 多关联任务的自主强化学习

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-06-04 DOI: 10.1109/DEVLRN.2019.8850713

V. Santucci, G. Baldassarre, Emilio Cartoni

引用次数: 24

Self-supervised Body Image Acquisition Using a Deep Neural Network for Sensorimotor Prediction 基于深度神经网络的自监督身体图像采集用于感觉运动预测

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-06-03 DOI: 10.1109/DEVLRN.2019.8850717

Alban Laflaquière, V. Hafner

引用次数: 6

An Optimization Framework for Task Sequencing in Curriculum Learning 课程学习任务排序的优化框架

2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2019-01-31 DOI: 10.1109/DEVLRN.2019.8850690

Francesco Foglino, M. Leonetti

引用次数: 14