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检索条件"任意字段=2012 IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL 2012"

共 594 条记录，以下是81-90 订阅

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Incremental learning of an optical flow model for sensorimotor anticipation in a mobile robot

Incremental learning of an optical flow model for sensorimot...

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2012 ieee international conference on development and learning and epigenetic robotics, icdl 2012

作者： Ribes, Arturo Cerquides, Jesús Demiris, Yiannis De Mántaras, Ramón López IIIA-CSIC - Campus UAB 08290 Bellaterra Barcelona Spain Department of Electrical and Electronic Engineering Imperial College London SW7 2BT United Kingdom

ISBN: (纸本)9781467349635

关键词： Optical flows

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Autonomous Reinforcement learning of Multiple Interrelated Tasks 9

Autonomous Reinforcement Learning of Multiple Interrelated T...

引用

9th Joint ieee international conference on development and learning and epigenetic robotics (icdl-EpiRob)

作者： Santucci, Vieri Giuliano Baldassarre, Gianluca Cartoni, Emilio CNR Ist Sci & Tecnol Cogniz Rome Italy

ISBN: (纸本)9781538681282

Autonomous multiple tasks learning is a fundamental capability to develop versatile artificial agents that can act in complex environments. In real-world scenarios, tasks may be interrelated (or "hierarchical") so that a robot has to first learn to achieve some of them to set the preconditions for learning other ones. Even though different strategies have been used in robotics to tackle the acquisition of interrelated tasks, in particular within the developmental robotics framework, autonomous learning in this kind of scenarios is still an open question. Building on previous research in the framework of intrinsically motivated open-ended learning, in this work we describe how this question can be addressed working on the level of task selection, in particular considering the multiple interrelated tasks scenario as an MDP where the system is trying to maximise its competence over all the tasks.

关键词： Multiple Interrelated Tasks Intrinsic Motivations Hierarchical Skill learning Reinforcement learning Autonomous robotics

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learning Spatial Relations Between Objects From 3D Scenes

Learning Spatial Relations Between Objects From 3D Scenes

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ieee 3rd Joint international conference on development and learning and epigenetic robotics (icdl)

作者： Fichtl, Severin Alexander, John Guerin, Frank Mustafa, Wail Kraft, Dirk Krueger, Norbert Univ Aberdeen Aberdeen AB24 3UE Scotland Maersk Mc Kinney Moller Inst DK-5230 Odense Denmark

""In this work, we learn a limited number of abstractions which can then be used to form preconditions for motor actions. These abstractions take the form of spatial relations amongst objects. We consider th... 详细信息

ISBN: (纸本)9781479910366

关键词： learning (artificial intelligence) robot vision

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Intensity Measurement of Spontaneous Facial Actions: Evaluation of Different Image Representations

Intensity Measurement of Spontaneous Facial Actions: Evaluat...

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ieee international conference on development and learning and epigenetic robotics (icdl)

作者： Zaker, Nazanin Mahoor, Mohammad H. Mattson, Whitney I. Messinger, Daniel S. Cohn, Jeffrey F. Univ Denver Dept Elect & Comp Engn Denver CO 80208 USA Univ Miami Dept Psychol Coral Gables FL 33146 USA Univ Pittsburgh Dept Psychol Pittsburgh PA 15260 USA

ISBN: (纸本)9781467349635;9781467349642

Intensity measurements of infant facial expressions are central to understand emotion-mediated interactions and emotional development. We evaluate alternative image representations for automatic measurement of the intensity of spontaneous facial Action Units (AUs) related to infant emotion expression. Twelve infants were video-recorded during face-to-face interactions with their mothers. Facial features were tracked using active appearance models (AAMs) and registered to a canonical view. Three feature representations were compared: shape and grey scale texture, Histogram of Oriented Gradients (HOG), and Local Binary Pattern Histograms (LBPH). To reduce the high dimensionality of the appearance features (grey scale texture, HOG, and LBPH), a non-linear algorithm was used (Laplacian Eigenmaps). For each representation, support vector machine classifiers were used to learn six gradations of AU intensity (0 to maximal). The target AUs were those central to positive and negative infant emotion. Shape plus grey scale texture performed best for AUs that involve non-rigid deformations of permanent facial features (e.g., AU 12 and AU 20). These findings suggest that AU intensity detection may be maximized by choosing feature representations best suited for specific AU.

关键词： image representation intensity measurement African Union ASTRONOMICAL UNIT Gold Grey scale AUTOMATIC MEASUREMENT METHODS Emotional development Australia Infant Facial Features

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Utilizing Pragmatic Frames as an analytical tool for children's performance during word learning 9

Utilizing Pragmatic Frames as an analytical tool for childre...

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9th Joint ieee international conference on development and learning and epigenetic robotics (icdl-EpiRob)

作者： Rohlfing, Katharina J. Grimminger, Angela Paderborn Univ Psycholinguist Paderborn Germany

ISBN: (纸本)9781538681282

Typically, to assess children's performance in a word learning task, a category coding is applied to the answers given by the children, according to which they can score "1" when correct and "0" when incorrect. This paper extends the current methodology: Following a recently re-introduced theory of Pragmatic Frames, the construct of Pragmatic Frames is proposed as an analytical tool which makes it possible (1) to describe children's performance in more detail and (2) to gain more insight into their pragmatic competencies.

关键词： pragmatics word learning Pragmatic Frames

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Intrinsically Motivated Multimodal Structure learning

Intrinsically Motivated Multimodal Structure Learning

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ieee Joint international conference on development and learning and epigenetic robotics (icdl-EpiRob)

作者： Wong, Jay Ming Grupen, Roderic A. Draper Lab Planning Auton & Automat Grp Cambridge MA 02139 USA Univ Massachusetts Coll Informat & Comp Sci Lab Perceptual Robot Amherst MA 01003 USA

ISBN: (纸本)9781509050697

We present a long-term intrinsically motivated structure learning method for modeling transition dynamics during controlled interactions between a robot and semipermanent structures in the world. These structures serve as the basis for a number of possible future tasks defined as Markov Decision Processes (MDPs). We apply a structure learning technique to a multimodal affordance representation that yields a population of forward models for use in planning. We evaluate the approach using experiments on a bimanual mobile manipulator (uBot-6) that show the performance of model acquisition as the number of transition actions increases.

关键词： Markov processes

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Continuous Adaptive Reinforcement learning with the Evolution of Self Organizing Classifiers

Continuous Adaptive Reinforcement Learning with the Evolutio...

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ieee 3rd Joint international conference on development and learning and epigenetic robotics (icdl)

作者： Vargas, Danilo Vasconcellos Takano, Hirotaka Murata, Junichi Kyushu Univ Grad Sch Informat Sci & Elect Engn Fukuoka 812 Japan Kyushu Univ Fac Informat Sci & Elect Engn Fukuoka 812 Japan

ISBN: (纸本)9781479910366

learning classifier systems have been solving reinforcement learning problems for some time. However, they face difficulties under multi-step continuous problems. Adaptation may also become harder with time since the convergence of the population decreases its diversity. This article demonstrate that the novel Self Organizing Classifiers method can cope with dynamical multi-step continuous problems. Moreover, adaptation remains the same after convergence.

关键词： adaptive systems convergence evolutionary computation learning (artificial intelligence) pattern classification self-organising feature maps

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Action Understanding using an Adaptive Liquid State Machine based on Environmental Ambiguity

Action Understanding using an Adaptive Liquid State Machine ...

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ieee 3rd Joint international conference on development and learning and epigenetic robotics (icdl)

作者： Baraglia, Jimmy Nagai, Yukie Asada, Minoru Osaka Univ Grad Sch Engn Dept Adapt Machine Syst Suita Osaka Japan

ISBN: (纸本)9781479910366

Recently, humans-robots interaction steps aside the traditional master/slave relationship to evolve in a new paradigm of cognitive robotics. Their conception requires the comprehension of human cognitive functions and how they develop. In this paper, we present how an adaptive Liquid State Machine using environment ambiguity may lead to a better emergence of action prediction abilities in a simple robot. The simulation results indicate the efficiency of the proposed method by which a simple robot develop its own prediction capability. These results are promising towards building robots able to develop more complicated capability such as understanding others' intention and further, cooperation with other agents.

关键词： cognitive systems human-robot interaction learning systems

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learning Versatile Sensorimotor Coordination with Goal Babbling and Neural Associative Dynamics

Learning Versatile Sensorimotor Coordination with Goal Babbl...

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ieee 3rd Joint international conference on development and learning and epigenetic robotics (icdl)

作者： Reinhart, Rene Felix Rolf, Matthias Univ Bielefeld Res Inst Cognit & Robot CoR Lab Bielefeld Germany

ISBN: (纸本)9781479910366

We combine an efficient exploration mechanism for bootstrapping of sensorimotor coordination skills with an associative network model to represent multiple coordination styles. Both approaches are integrated into a three-phased process of exploration, i.e. discovery of a new model, consolidation, the long-term storage of multiple models in a dynamical associative network, and exploitation of multiple models by the neural dynamics for versatile sensorimotor coordination. The proposed exploration-consolidation process is demonstrated for a planar robotic manipulator with ten degrees of freedom. Exploitation of sensorimotor coordination from the consolidated neural dynamics features motor hysteresis and additionally comprises a forward model that can be utilized to interpret proprioceptive feedback.

关键词： content-addressable storage learning (artificial intelligence) manipulator dynamics neurocontrollers

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A Bio-Inspired Attention Model of Anticipation in Gaze-Contingency Experiments with Infants

A Bio-Inspired Attention Model of Anticipation in Gaze-Conti...

引用

ieee international conference on development and learning and epigenetic robotics (icdl)

作者： Marraffa, Rodolfo Sperati, Valerio Caligiore, Daniele Triesch, Jochen Baldassarre, Gianluca Univ Rome Dipartimento Filosofia Rome Italy Consiglio Nazl Rich Ist Sci Tec Cogn Rome Italy Frankfurt Inst Adv Studies Frankfurt Germany

ISBN: (纸本)9781467349635;9781467349642

The empirical investigation of cognitive processes in infants is hampered by the limited development of their body and motor control skills. Novel gaze-contingent paradigms where infants control their environment with their eyes offer a solution to this problem since the control of gaze develops very early. Recently such a paradigm has been used to investigate the learning of anticipatory behaviour of 6/8-months-old infants in an experiment where gazing at a "button" causes the appearance of an interesting image. The experiment shows that infants learn in few trials to "press the button" with their gaze and, remarkably, to anticipate the image appearance in only few trials. The experiment raises two questions: (a) what are the processes supporting such fast learning? (b) why does the anticipatory behaviour emerge? This paper presents a bio-inspired model that puts forward possible answers to these questions. The model consists of: (a) a bottom-up attention component for scene saliency detection;(b) a top-down attention component that uses reinforcement learning (RL) to learn to control gaze based on current foveal stimuli;(c) a dynamic field map that decides where to look based on the bottom-up and top-down information. The results show that the model is indeed capable of learning to perform anticipatory saccades in few trials. The analysis of the system shows that this fast learning is due to the guidance exerted by the bottom-up component on the learning process of the top-down component. Moreover, it shows that the anticipatory behaviour can be explained in terms of the action of the top-down component exploiting the learned spatial relations of stimuli in an anticipatory fashion. Overall, the results indicate that the model has the essential features to theoretically frame, interpret, and design experiments using gaze contingency.

关键词： Ocular Fixation Infant Predictive anticipation top-down bottom-up learning experimentation

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