2008 7th IEEE International Conference on Development and Learning最新文献_第2页

Sensorimotor abstraction selection for efficient, autonomous robot skill acquisition 高效自主机器人技能习得的感觉运动抽象选择

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640821

G. Konidaris, A. Barto

引用次数: 16

The role of observational learning in perceiving pbject properties in infants (March 2008) 观察学习在婴儿感知客体属性中的作用(2008年3月)

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640829

J. Fagard, R. Esseily, J. Nadel

{"title":"The role of observational learning in perceiving pbject properties in infants (March 2008)","authors":"J. Fagard, R. Esseily, J. Nadel","doi":"10.1109/DEVLRN.2008.4640829","DOIUrl":"https://doi.org/10.1109/DEVLRN.2008.4640829","url":null,"abstract":"Infants become skilful at manipulating objects around the end of the first year of life. The question asked here is how do they learn about object properties and what is the role of observation in learning to manipulate objects. In order to answer these questions we designed an experiment where we compared the effect of practice versus observation on learning new motor skills. We tested 84 infants aged 8, 10, 12, 15 and 18 months on two different tasks: a simple grasping task and a more complex retrieval task. We compared two groups of infants: an observation group where the experimenter presented directly the infants with the demonstration of the targeted action and then gave the infant the object to manipulate; and a self-exploratory group where infants were presented with a spontaneous trial before the demonstration. The results show that for a simple grasping task, only the youngest infants benefit both from practice and observation because of their poor performance at the very first, spontaneous, trial. As for the retrieval task, infants learned only by observation and not before 15 month of age.","PeriodicalId":366099,"journal":{"name":"2008 7th IEEE International Conference on Development and Learning","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117035146","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

Detection and categorization of facial image through the interaction with caregiver

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640837

M. Ogino, A. Watanabe, M. Asada

引用次数: 10

Building a more effective teaching robot using apprenticeship learning 利用学徒制学习构建更有效的教学机器人

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640831

P. Ruvolo, Jacob Whitehill, Marjo Vimes, J. Movellan

{"title":"Building a more effective teaching robot using apprenticeship learning","authors":"P. Ruvolo, Jacob Whitehill, Marjo Vimes, J. Movellan","doi":"10.1109/DEVLRN.2008.4640831","DOIUrl":"https://doi.org/10.1109/DEVLRN.2008.4640831","url":null,"abstract":"What defines good teaching? While attributes such as timing, responsiveness to social cues, and pacing of material clearly play a role, it is difficult to create a comprehensive specification of what it means to be a good teacher. On the other hand, it is relatively easy to obtain examples of expert teaching behavior by observing a real teacher. With this inspiration as our guide, we investigated apprenticeship learning methods [1] that use data recorded from expert teachers as a means of improving the teaching abilities of RUBI, a social robot immersed in a classroom of 18-24 month old children. While this approach has achieved considerable success in mechanical control, such as automated helicopter flight [2], until now there has been little work on applying it to the field of social robotics. This paper explores two particular approaches to apprenticeship learning, and analyzes the models of teaching that each approach learns from the data of the human teacher. Empirical results indicate that the apprenticeship learning paradigm, though still nascent in its use in the social robotics field, holds promise, and that our proposed methods can already extract meaningful teaching models from demonstrations of a human expert.","PeriodicalId":366099,"journal":{"name":"2008 7th IEEE International Conference on Development and Learning","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126602465","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: 13

Acquiring linguistic argument structure from multimodal input using attentive focus 利用注意焦点从多模态输入获取语言论证结构

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640803

G. Satish, A. Mukerjee

{"title":"Acquiring linguistic argument structure from multimodal input using attentive focus","authors":"G. Satish, A. Mukerjee","doi":"10.1109/DEVLRN.2008.4640803","DOIUrl":"https://doi.org/10.1109/DEVLRN.2008.4640803","url":null,"abstract":"This work is premised on three assumptions: that the semantics of certain actions may be learned prior to language, that objects in attentive focus are likely to indicate the arguments participating in that action, and that knowing such arguments helps align linguistic attention on the relevant predicate (verb). Using a computational model of dynamic attention, we present an algorithm that clusters visual events into action classes in an unsupervised manner using the Merge Neural Gas algorithm. With few clusters, the model correlates to coarse concepts such as come-closer, but with a finer granularity, it reveals hierarchical substructure such as come-closer-one-object-static and come-closer-both-moving. That the argument ordering is non-commutative is discovered for actions such as chase or come-closer-one-object-static. Knowing the arguments, and given that noun-referent mappings that are easily learned, language learning can now be constrained by considering only linguistic expressions and actions that refer to the objects in perceptual focus. We learn action schemas for linguistic units like ldquomoving towardsrdquo or ldquochaserdquo, and validate our results by producing output commentaries for 3D video.","PeriodicalId":366099,"journal":{"name":"2008 7th IEEE International Conference on Development and Learning","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133507992","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: 12

Modeling the development of overselectivity in autism 自闭症过度选择的发展模型

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640809

T. Kriete, D. Noelle

{"title":"Modeling the development of overselectivity in autism","authors":"T. Kriete, D. Noelle","doi":"10.1109/DEVLRN.2008.4640809","DOIUrl":"https://doi.org/10.1109/DEVLRN.2008.4640809","url":null,"abstract":"People with autism consistently demonstrate a lack sensitivity to the full range of important aspects of everyday situations. Often, an overly restricted subset of the information available in a given situation gains control over their behavior. This can result in problems generalizing learned behaviors to novel situations. This phenomenon has been called overselectivity. Indeed, many behavioral intervention techniques seek to mitigate overselectivity effects in this population. In this paper, we offer an account of overselectivity as arising from an inability to flexibly adjust the attentional influences of the prefrontal cortex on behavior. We posit that dysfunctional dopamine interactions with the prefrontal cortex result in overly perseverative attention in people with autism. Limiting attention to only a few of the features of a situation hinders the learning of associations between the full range of relevant environmental properties and appropriate behavior. Thus, a restricted subset of features gain control over responding. A simple neurocomputational model of the attentional effects of prefrontal cortex on learning is presented, demonstrating how weak dopamine modulation of frontal areas can lead to overselectivity.","PeriodicalId":366099,"journal":{"name":"2008 7th IEEE International Conference on Development and Learning","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132228124","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: 4

Visual attention by saliency leads cross-modal body representation 显著性视觉注意导致跨模态身体表征

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640822

M. Hikita, S. Fuke, M. Ogino, T. Minato, M. Asada

{"title":"Visual attention by saliency leads cross-modal body representation","authors":"M. Hikita, S. Fuke, M. Ogino, T. Minato, M. Asada","doi":"10.1109/DEVLRN.2008.4640822","DOIUrl":"https://doi.org/10.1109/DEVLRN.2008.4640822","url":null,"abstract":"One of the most fundamental issues for physical agents (humans, primates, and robots) in performing various kinds of tasks is body representation. Especially during tool-use by monkeys, neurophysiological evidence shows that the representation can be dynamically reconstructed by spatio-temporal integration of different sensor modalities so that it can be adaptive to environmental changes. However, to construct such a representation, an issue to be resolved is how to associate which information among various sensory data. This paper presents a method that constructs cross-modal body representation from vision, touch, and proprioception. Tactile sensation, when the robot touches something, triggers the construction process of the visual receptive field for body parts that can be found by visual attention based on a saliency map and consequently regarded as the end effector. Simultaneously, proprioceptive information is associated with this visual receptive field to achieve the cross-modal body representation. The proposed model is applied to a real robot and results comparable to the activities of parietal neurons observed in monkeys are shown.","PeriodicalId":366099,"journal":{"name":"2008 7th IEEE International Conference on Development and Learning","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116132352","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: 32

Input affects uptake: How early language experience influences processing efficiency and vocabulary learning 输入影响吸收:早期语言经验如何影响加工效率和词汇学习

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640802

A. Fernald, V. Marchman, Nereyda Hurtado

引用次数: 22

Acquisition of lexical semantics through unsupervised discovery of associations between perceptual symbols 通过无监督地发现知觉符号之间的关联而获得词汇语义

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640799

T. Oezer

引用次数: 2

Ockham’s razor as inductive bias in preschooler’s causal explanations 奥卡姆剃刀在学龄前儿童因果解释中的归纳偏差

2008 7th IEEE International Conference on Development and Learning Pub Date : 2008-10-10 DOI: 10.1109/DEVLRN.2008.4640797

E. B. Bonawitz, Isabel Y. Chang, Catherine Clark, Tania Lombrozo

引用次数: 5