2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL)最新文献_第4页

An Enactive approach to autonomous agent and robot learning 自主智能体和机器人学习的一种主动方法

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652527

Olivier L. Georgeon, Christian Wolf, S. L. Gay

引用次数: 9

Dynamic shift in isolating referents: From social to self-generated input 孤立指涉物的动态转变:从社会输入到自我生成输入

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652570

Hanako Yoshida, Joseph M. Burling

引用次数: 4

Action understanding using an adaptive Liquid State Machine based on environmental ambiguity 基于环境模糊性的自适应液态机的动作理解

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652528

Jimmy Baraglia, Y. Nagai, M. Asada

引用次数: 5

Continuous adaptive reinforcement learning with the evolution of Self Organizing Classifiers 基于自组织分类器进化的持续自适应强化学习

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652558

Danilo Vasconcellos Vargas, H. Takano, J. Murata

引用次数: 3

Combining synchrony and shape detection to sustain the robot focus of attention on a selected human partner 将同步和形状检测相结合，使机器人的注意力集中在选定的人类伴侣上

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652529

C. Grand, Ghilès Mostafaoui, Syed Khursheed Hasnain, P. Gaussier

{"title":"Combining synchrony and shape detection to sustain the robot focus of attention on a selected human partner","authors":"C. Grand, Ghilès Mostafaoui, Syed Khursheed Hasnain, P. Gaussier","doi":"10.1109/DEVLRN.2013.6652529","DOIUrl":"https://doi.org/10.1109/DEVLRN.2013.6652529","url":null,"abstract":"The present study deals with the problematic of attentional mechanism allowing to initiate and to maintain Human Robot Interactions (HRI) by orienting the robot's visual focus on interacting human partners. In our previous work, we took inspiration from human psychological and neurological data which suggest that synchrony is an important parameter for human-human interaction. We proposed synchrony as a way of interacting and presented a synchrony-based architecture capable of selecting the human partner and of locating the focus of attention. To deal with the problematic of initiating the HRI, we proposed, in our recent works, a neural model permitting to focus the robot visual attention on a selected partner on the basis of synchrony detection between its own dynamics and the human movements. This model maintain the interaction and the robot's focus of attention while the partner moves in synchrony. Consequently, the interaction is interrupted if the partner stops moving. For a more realist HRI, the agents have to be able to switch their roles (turn tacking), as a result, they could alternate moving and static interaction phases. In this case, we propose here to complete the previous neural model by adding a shape based attentional mechanism. After initiating the interaction on the basis of synchrony, the robot will automatically learn to recognize the selected partner and maintain its attention with the human during unsynchronized phases of interaction.","PeriodicalId":106997,"journal":{"name":"2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123269699","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: 0

Exploration strategies in developmental robotics: A unified probabilistic framework 发展机器人的探索策略:一个统一的概率框架

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652535

Clément Moulin-Frier, Pierre-Yves Oudeyer

引用次数: 53

Touch and emotion: Modeling of developmental differentiation of emotion lead by tactile dominance 触觉与情感:触觉优势导致的情感发育分化模型

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652538

Takato Horii, Y. Nagai, M. Asada

{"title":"Touch and emotion: Modeling of developmental differentiation of emotion lead by tactile dominance","authors":"Takato Horii, Y. Nagai, M. Asada","doi":"10.1109/DEVLRN.2013.6652538","DOIUrl":"https://doi.org/10.1109/DEVLRN.2013.6652538","url":null,"abstract":"Emotion is one of the important elements for humans to communicate with others. Humans are known to share basic emotions such as joy and anger although their developmental changes have been studied less. We propose a computational model for the emotional development in infancy. Our model reproduces the differentiation of emotion from pleasant/unpleasant states to six basic emotions as known in psychological studies. The key idea is twofold: the tactile dominance in infant-caregiver interaction and the inherent ability of tactile sense to discriminate pleasant/unpleasant states. Our model consists of probabilistic neural networks called Restricted Boltzmann Machines. The networks are hierarchically organized to first extract important features from tactile, auditory, and visual stimuli and then to integrate them to represent an emotional state. Pleasant/unpleasant information is directly provided to the highest level of the network to facilitate the emotional differentiation. Experimental results show that our model with the tactile dominance leads to better differentiation of emotion than others without such dominance.","PeriodicalId":106997,"journal":{"name":"2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125721863","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

Autonomous learning based on depth perception and behavior generation 基于深度感知和行为生成的自主学习

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652531

Sungmoon Jeong, Yunjung Park, Minho Lee

引用次数: 0

Frustration as a way toward autonomy and self-improvement in robotic navigation 挫折是机器人导航走向自主和自我完善的一种方式

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652540

Adrien Jauffret, Marwen Belkaid, N. Cuperlier, P. Gaussier, P. Tarroux

{"title":"Frustration as a way toward autonomy and self-improvement in robotic navigation","authors":"Adrien Jauffret, Marwen Belkaid, N. Cuperlier, P. Gaussier, P. Tarroux","doi":"10.1109/DEVLRN.2013.6652540","DOIUrl":"https://doi.org/10.1109/DEVLRN.2013.6652540","url":null,"abstract":"Autonomy and self-improvement capabilities are still challenging in the field of robotics. Allowing a robot to autonomously navigate in wide and unknown environments not only requires a set of robust strategies to cope with miscellaneous situations, but also needs mechanisms of self-assessment for guiding learning and for monitoring strategies. Monitoring strategies requires feedbacks on the behavior's quality, from a given fitness system in order to take correct decisions. In this work, we focus on how an emotional controller can be used to modulate robot behaviors. Following an incremental and constructivist approach, we present a generic neural architecture, based on an online novelty detection algorithm that may be able to evaluate any sensory-motor strategies. This architecture learns contingencies between sensations and actions, giving the expected sensation from the past perception. Prediction error, coming from surprising events, provides a direct measure of the quality of the underlying sensory-motor contingencies involved. We show how a simple emotional controller based on the prediction progress allows the system to regulate its behavior to solve complex navigation tasks and to communicate its disability in deadlock situations. We propose that this model could be a key structure toward self-monitoring. We made several experiments that can account for such properties with different behaviors (road following and place cells based navigation).","PeriodicalId":106997,"journal":{"name":"2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133906341","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

Do humans need learning to read humanoid lifting actions? 人类需要学习解读人形举重动作吗?

2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL) Pub Date : 2013-11-04 DOI: 10.1109/DEVLRN.2013.6652557

A. Sciutti, Laura Patanè, F. Nori, G. Sandini

{"title":"Do humans need learning to read humanoid lifting actions?","authors":"A. Sciutti, Laura Patanè, F. Nori, G. Sandini","doi":"10.1109/DEVLRN.2013.6652557","DOIUrl":"https://doi.org/10.1109/DEVLRN.2013.6652557","url":null,"abstract":"Humans can infer, just from the observation of others' actions, several information on the actor's intents and on the properties of the manipulated objects. This intuitive understanding is very efficient and allows two collaborating partners to be prepared to handle the common tools, as they can estimate the weight of the object the other agent is passing to them even before the hand-over is concluded. Transferring this kind of mutual understanding to human - robot interactions would be particularly beneficial, as it would improve the fluidity of any collaborative task. The question that we address in this study is therefore under which conditions humans can estimate the weight lifted by a humanoid robot and whether the acquisition of this skill requires an extensive learning by the human subject. Moreover, we assess whether reading humanoid lifting actions implies the involvement of the observer's motor system, as it happens for weight judgment from the observation of human actions. Our results indicate that with a proper design of the humanoid lifting motions, human subjects are able to estimate the weight lifted by the humanoid robot with a similar accuracy as that exhibited during human observation. Furthermore, such ability is intuitive and does not require learning or training. Lastly, weight judgment seems to be dependent on the involvement of the observer's motor system both during human and humanoid observation. These findings suggest that the neural mechanisms at the basis of human interaction can be extended to human-humanoid interaction, allowing for intuitive and proficient collaboration between humanoid robots and untrained human partners.","PeriodicalId":106997,"journal":{"name":"2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114613063","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: 11