IEEE Transactions on Autonomous Mental Development最新文献_第6页

Object Learning Through Active Exploration 通过主动探索的对象学习

IEEE Transactions on Autonomous Mental Development Pub Date : 2014-03-01 DOI: 10.1109/TAMD.2013.2280614

S. Ivaldi, S. Nguyen, Natalia Lyubova, Alain Droniou, V. Padois, David Filliat, Pierre-Yves Oudeyer, Olivier Sigaud

引用次数: 69

Development of First Social Referencing Skills: Emotional Interaction as a Way to Regulate Robot Behavior 第一社会参照技能的发展:情感互动是调节机器人行为的一种方式

IEEE Transactions on Autonomous Mental Development Pub Date : 2014-03-01 DOI: 10.1109/TAMD.2013.2284065

S. Boucenna, P. Gaussier, L. Hafemeister

引用次数: 22

Erratum to "Modeling cross-modal interactions in early word learning" [Dec 13 288-297] 对“早期单词学习中跨模态交互建模”的勘误[Dec 13 288-297]

IEEE Transactions on Autonomous Mental Development Pub Date : 2014-03-01 DOI: 10.1109/TAMD.2014.2310061

Nadja Althaus, D. Mareschal

引用次数: 0

LIDA: A Systems-level Architecture for Cognition, Emotion, and Learning LIDA:用于认知、情感和学习的系统级架构

IEEE Transactions on Autonomous Mental Development Pub Date : 2014-03-01 DOI: 10.1109/TAMD.2013.2277589

S. Franklin, Tamas Madl, S. D’Mello, Javier Snaider

{"title":"LIDA: A Systems-level Architecture for Cognition, Emotion, and Learning","authors":"S. Franklin, Tamas Madl, S. D’Mello, Javier Snaider","doi":"10.1109/TAMD.2013.2277589","DOIUrl":"https://doi.org/10.1109/TAMD.2013.2277589","url":null,"abstract":"We describe a cognitive architecture learning intelligent distribution agent (LIDA) that affords attention, action selection and human-like learning intended for use in controlling cognitive agents that replicate human experiments as well as performing real-world tasks. LIDA combines sophisticated action selection, motivation via emotions, a centrally important attention mechanism, and multimodal instructionalist and selectionist learning. Empirically grounded in cognitive science and cognitive neuroscience, the LIDA architecture employs a variety of modules and processes, each with its own effective representations and algorithms. LIDA has much to say about motivation, emotion, attention, and autonomous learning in cognitive agents. In this paper, we summarize the LIDA model together with its resulting agent architecture, describe its computational implementation, and discuss results of simulations that replicate known experimental data. We also discuss some of LIDA's conceptual modules, propose nonlinear dynamics as a bridge between LIDA's modules and processes and the underlying neuroscience, and point out some of the differences between LIDA and other cognitive architectures. Finally, we discuss how LIDA addresses some of the open issues in cognitive architecture research.","PeriodicalId":49193,"journal":{"name":"IEEE Transactions on Autonomous Mental Development","volume":"6 1","pages":"19-41"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TAMD.2013.2277589","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62762073","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: 184

Editorial TAMD Update 编辑更新

IEEE Transactions on Autonomous Mental Development Pub Date : 2014-01-01 DOI: 10.1109/TAMD.2014.2309431

Zhengyou Zhang

引用次数: 0

Introduction of New Associate Editors 新副编辑的介绍

IEEE Transactions on Autonomous Mental Development Pub Date : 2014-01-01 DOI: 10.1109/TAMD.2014.2309443

Zhengyou Zhang

引用次数: 0

Modeling Cross-Modal Interactions in Early Word Learning 早期单词学习中的跨模态交互建模

IEEE Transactions on Autonomous Mental Development Pub Date : 2013-12-01 DOI: 10.1109/TAMD.2013.2264858

Nadja Althaus, D. Mareschal

引用次数: 12

Computational Audiovisual Scene Analysis in Online Adaptation of Audio-Motor Maps 音频-运动地图在线适配中的计算视听场景分析

IEEE Transactions on Autonomous Mental Development Pub Date : 2013-12-01 DOI: 10.1109/TAMD.2013.2257766

Rujiao Yan, Tobias Rodemann, B. Wrede

{"title":"Computational Audiovisual Scene Analysis in Online Adaptation of Audio-Motor Maps","authors":"Rujiao Yan, Tobias Rodemann, B. Wrede","doi":"10.1109/TAMD.2013.2257766","DOIUrl":"https://doi.org/10.1109/TAMD.2013.2257766","url":null,"abstract":"For sound localization, the binaural auditory system of a robot needs audio-motor maps, which represent the relationship between certain audio features and the position of the sound source. This mapping is normally learned during an offline calibration in controlled environments, but we show that using computational audiovisual scene analysis (CAVSA), it can be adapted online in free interaction with a number of a priori unknown speakers. CAVSA enables a robot to understand dynamic dialog scenarios, such as the number and position of speakers, as well as who is the current speaker. Our system does not require specific robot motions and thus can work during other tasks. The performance of online-adapted maps is continuously monitored by computing the difference between online-adapted and offline-calibrated maps and also comparing sound localization results with ground truth data (if available). We show that our approach is more robust in multiperson scenarios than the state of the art in terms of learning progress. We also show that our system is able to bootstrap with a randomized audio-motor map and adapt to hardware modifications that induce a change in audio-motor maps.","PeriodicalId":49193,"journal":{"name":"IEEE Transactions on Autonomous Mental Development","volume":"5 1","pages":"273-287"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TAMD.2013.2257766","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62761367","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

A Robotic Model of Reaching and Grasping Development 机器人的伸手与抓握发展模型

IEEE Transactions on Autonomous Mental Development Pub Date : 2013-12-01 DOI: 10.1109/TAMD.2013.2264321

Piero Savastano, S. Nolfi

引用次数: 21

Learning to Reproduce Fluctuating Time Series by Inferring Their Time-Dependent Stochastic Properties: Application in Robot Learning Via Tutoring 通过推断波动时间序列的随时间随机特性来学习再现波动时间序列:在机器人辅导学习中的应用

IEEE Transactions on Autonomous Mental Development Pub Date : 2013-12-01 DOI: 10.1109/TAMD.2013.2258019

Shingo Murata, Jun Namikawa, H. Arie, S. Sugano, J. Tani

{"title":"Learning to Reproduce Fluctuating Time Series by Inferring Their Time-Dependent Stochastic Properties: Application in Robot Learning Via Tutoring","authors":"Shingo Murata, Jun Namikawa, H. Arie, S. Sugano, J. Tani","doi":"10.1109/TAMD.2013.2258019","DOIUrl":"https://doi.org/10.1109/TAMD.2013.2258019","url":null,"abstract":"This study proposes a novel type of dynamic neural network model that can learn to extract stochastic or fluctuating structures hidden in time series data. The network learns to predict not only the mean of the next input state, but also its time-dependent variance. The training method is based on maximum likelihood estimation by using the gradient descent method and the likelihood function is expressed as a function of the estimated variance. Regarding the model evaluation, we present numerical experiments in which training data were generated in different ways utilizing Gaussian noise. Our analysis showed that the network can predict the time-dependent variance and the mean and it can also reproduce the target stochastic sequence data by utilizing the estimated variance. Furthermore, it was shown that a humanoid robot using the proposed network can learn to reproduce latent stochastic structures hidden in fluctuating tutoring trajectories. This learning scheme is essential for the acquisition of sensory-guided skilled behavior.","PeriodicalId":49193,"journal":{"name":"IEEE Transactions on Autonomous Mental Development","volume":"10 1","pages":"298-310"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TAMD.2013.2258019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62761375","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: 62