2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)最新文献_第2页

Cognitive robotics for the modelling of cognitive dysfunctions: A study on unilateral spatial neglect 认知机器人对认知功能障碍的建模:对单侧空间忽视的研究

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346161

D. Conti, S. Nuovo, A. D. Nuovo

引用次数: 1

Biological and simulated neuronal networks show similar competence on a visual tracking task 生物神经网络和模拟神经网络在视觉跟踪任务上表现出相似的能力

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346153

Abraham M. Shultz, Sangmook Lee, T. Shea, H. Yanco

引用次数: 3

A Deep Learning Neural Network for Number Cognition: A bi-cultural study with the iCub 数字认知的深度学习神经网络:与iCub的双文化研究

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346165

A. D. Nuovo, V. Cruz, A. Cangelosi

{"title":"A Deep Learning Neural Network for Number Cognition: A bi-cultural study with the iCub","authors":"A. D. Nuovo, V. Cruz, A. Cangelosi","doi":"10.1109/DEVLRN.2015.7346165","DOIUrl":"https://doi.org/10.1109/DEVLRN.2015.7346165","url":null,"abstract":"The novel deep learning paradigm offers a highly biologically plausible way to train neural network architectures with many layers, inspired by the hierarchical organization of the human brain. Indeed, deep learning gives a new dimension to research modeling human cognitive behaviors, and provides new opportunities for applications in cognitive robotics. In this paper, we present a novel deep neural network architecture for number cognition by means of finger counting and number words. The architecture is composed of 5 layers and is designed in a way that allows it to learn numbers from one to ten by associating the sensory inputs (motor and auditory) coming from the iCub humanoid robotic platform. The architecture performance is validated and tested in two developmental experiments. In the first experiment, standard backpropagation is compared with a deep learning approach, in which weights and biases are pre-trained by means of a greedy algorithm and then refined with backpropagation. In the second experiment, six bi-cultural number learning conditions are compared to explore the impact of different languages (for number words) and finger counting strategies. The developmental experiments confirm the validity of the model and the increase in efficiency given by the deep learning approach. Results of the bi-cultural study are presented and discussed with respect to the neuro-psychological literature and implications of the results for learning situations are briefly outlined.","PeriodicalId":164756,"journal":{"name":"2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115828644","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: 18

Cross-situational noun and adjective learning in an interactive scenario 交互式情景下的跨情景名词和形容词学习

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346129

Yuxin Chen, David Filliat

引用次数: 12

A neural network model of curiosity-driven infant categorization 好奇心驱动婴儿分类的神经网络模型

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346097

Katherine E. Twomey, G. Westermann

{"title":"A neural network model of curiosity-driven infant categorization","authors":"Katherine E. Twomey, G. Westermann","doi":"10.1109/DEVLRN.2015.7346097","DOIUrl":"https://doi.org/10.1109/DEVLRN.2015.7346097","url":null,"abstract":"Infants are curious learners who drive their own cognitive development by imposing structure on their learning environments as they explore. Understanding the mechanisms underlying this curiosity is therefore critical to our understanding of development. However, very few studies have examined the role of curiosity in infants' learning, and in particular, their categorization; what structure infants impose on their own environment and how this affects learning is therefore unclear. The results of studies in which the learning environment is structured a priori are contradictory: while some suggest that complexity optimizes learning, others suggest that minimal complexity is optimal, and still others report a Goldilocks effect by which intermediate difficulty is best. We used an auto-encoder network to capture empirical data in which 10-month-old infants' categorization was supported by maximal complexity [1]. When we allowed the same model to choose stimulus sequences based on a “curiosity” metric which took into account the model's internal states as well as stimulus features, categorization was better than selection based solely on stimulus characteristics. The sequences of stimuli chosen by the model in the curiosity condition showed a Goldilocks effect with intermediate complexity. This study provides the first computational investigation of curiosity-based categorization, and points to the importance characterizing development as emerging from the relationship between the learner and its environment.","PeriodicalId":164756,"journal":{"name":"2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125094776","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

Cross-domain and within-domain synaptic maintenance for autonomous development of visual areas 跨域和域内突触维持对视觉区域自主发展的影响

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346118

Q. Guo, Xiaofeng Wu, J. Weng

{"title":"Cross-domain and within-domain synaptic maintenance for autonomous development of visual areas","authors":"Q. Guo, Xiaofeng Wu, J. Weng","doi":"10.1109/DEVLRN.2015.7346118","DOIUrl":"https://doi.org/10.1109/DEVLRN.2015.7346118","url":null,"abstract":"Where-What Networks (WWNs) is a series of developmental networks for the recognition and attention of complex visual scenes. One of the most critical challenges of autonomous development is task non-specificity, namely, the network is meant to learn a variety of open-ended task skills without pre-defined tasks. Then how does a brain-like network develop skills for object relation that can generalize using implicit symbol-like rules? A preliminary scheme of uniform synaptic maintenance, which works across a neuron's sensory and motor domains, has been proposed in our WWN-9. In the new work here, we show that cross-domain and within-domain synaptic maintenance gains superior generalization than using the uniform synaptic maintenance scheme. This generalization enables the WWN to automatically discover symbol-like but implicit rules - detecting object groups from new combinations of object locations that were never observed. By “symbol-like but implicit rules”, we mean that the development program has no symbols and explicit rules, but symbol-like concepts (location, type) and implicit rule (two specific type objects must present concurrently - group) emerge as the firing patterns of the motor area and are used by the control. Moreover, the process of synaptic maintenance corresponds to the genesis (and adaptation) of cell connections and our model autonomously develops the Y area into two subarea, early area and later area, in charge of pattern recognition and symbolic reasoning respectively.","PeriodicalId":164756,"journal":{"name":"2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"692 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123054127","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

The developing sense of agency: Implications from cognitive phenomenology 发展中的代理感:来自认知现象学的启示

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346126

L. Zaadnoordijk, S. Hunnius, M. Meyer, J. Kwisthout, I.J.E.I. van Rooij

引用次数: 4

Motor experience alters action perception through predictive learning of sensorimotor information 运动经验通过对感觉运动信息的预测性学习改变动作知觉

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346116

Jimmy Baraglia, Jorge Luis Copete, Y. Nagai, M. Asada

{"title":"Motor experience alters action perception through predictive learning of sensorimotor information","authors":"Jimmy Baraglia, Jorge Luis Copete, Y. Nagai, M. Asada","doi":"10.1109/DEVLRN.2015.7346116","DOIUrl":"https://doi.org/10.1109/DEVLRN.2015.7346116","url":null,"abstract":"Recent studies have revealed that infants' goal-directed action execution strongly alters their perception of similar actions performed by other individuals. Such an ability to recognize correspondences between self-experience and others' actions may be crucial for the development of higher cognitive social skills. However, there is not yet a computational model or constructive explanation accounting for the role of action generation in the perception of others' actions. We hypothesize that the sensory and motor information are integrated at a neural level through a predictive learning process. Thus, the experience of motor actions alters the representation of the sensorimotor integration, which causes changes in the perception of others' actions. To test this hypothesis, we built a computational model that integrates visual and motor (hereafter, visuomotor) information using a Recurrent Neural Network (RNN) which is capable of learning temporal sequences of data. We modeled the visual attention of the system based on a prediction error calculated as the difference between the predicted sensory values and the actual sensory values, which maximizes the attention toward not too predictable and not too unpredictable sensory information. We performed a series of experiments with a simulated humanoid robot. The experiments showed that the motor activation during self-generated actions biased the robot's perception of others' actions. These results highlight the important role of modalities integration in humans, which accounts for a biased perception of our environment based on a restricted repertoire of own experienced actions.","PeriodicalId":164756,"journal":{"name":"2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116086750","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

What accounts for developmental shifts in optic flow sensitivity? 什么解释了光流敏感性的发育变化?

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7345450

R. Gilmore, F. Raudies, S. Jayaraman

引用次数: 10

The development of cooperation in evolving populations through social importance 通过社会重要性在不断发展的人口中发展合作

2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) Pub Date : 2015-12-07 DOI: 10.1109/DEVLRN.2015.7346163

P. Sequeira, S. Mascarenhas, Francisco S. Melo, Ana Paiva

{"title":"The development of cooperation in evolving populations through social importance","authors":"P. Sequeira, S. Mascarenhas, Francisco S. Melo, Ana Paiva","doi":"10.1109/DEVLRN.2015.7346163","DOIUrl":"https://doi.org/10.1109/DEVLRN.2015.7346163","url":null,"abstract":"Several agent-based frameworks have been proposed to investigate the possible reasons that lead humans to act in the interest of others while giving up individual gains. In this paper we propose a novel framework for analyzing this phenomenon based on the notions of social importance (SI) and local discrimination. We analyze such mechanism in the context of a “favors game” where a recipient agent can “claim” a favor to a donor agent, which may in turn “confer” its request at the expense of a certain cost. We perform several agent-based simulations and study both the conditions under which cooperation occurs and the dynamics of the relationships formed within a population. The results of our study indicate that the SI mechanism can promote cooperation in populations where all individuals share a common social predisposition towards the favors game, and also in initially mixed-strategy populations evolving by means of mutation and natural selection. We also show that the framework predicts the emergence of a conservative strategy that makes individuals to be “cautious” when interacting with “acquaintances”.","PeriodicalId":164756,"journal":{"name":"2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)","volume":"7 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129236525","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