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Autonomous Mental Development, IEEE Transactions on

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ISSN (Print) 1943-0604
Published by Institute of Electrical and Electronics Engineers (IEEE)

[163 journals]

IEEE Computational Intelligence Society Information
- Pages: C3 - C3
  Abstract: Provides a listing of current committee members and society officers.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
IEEE Transactions on Autonomous Mental Development information for authors
- Pages: C4 - C4
  Abstract: Provides instructions and guidelines to prospective authors who wish to submit manuscripts.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
IEEE Transactions on Autonomous Mental Development publication information
- Pages: C2 - C2
  Abstract: Provides a listing of current staff, committee members and society officers.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Table of contents
- Pages: C1 - C1
  Abstract: Presents the cover/table of contents for this issue of the periodical.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Editorial - TAMD Outstanding Paper Award and Open Access Publication Established
- Authors: Zhang; Z.;
  Pages: 1 - 1
  Abstract: In an editorial of the IEEE Transactions on Autonomous Mental Development (TAMD) (Vol. 4, No. 3), the author noted the progress made in establishing the IEEE TAMD Outstanding Paper Award to recognize annually outstanding papers published in the TRANSACTIONS. He is pleased to report that the IEEE Technical Activities Board (TAB) has approved the motion and that the IEEE TAMD Outstanding Paper Award will be formally established in 2013. This is the first year the Award will be bestowed. For the current round of competition, any paper published in 2011 (Volume 3) is eligible for consideration. The prize includes a US$1000 honorarium, to be split equally among coauthors, and certificates to the author and coauthors of the selected paper. Please note, no self-nomination is allowed. On another topic, IEEE TAMD is a hybrid transactions allowing either traditional publications or author-pay Open Access (OA) publications. The OA option, if selected, enables unrestricted public access to the article via IEEE Xplore. The OA option will be offered to the author at the time the manuscript is submitted. If selected, the OA fee must be paid before the article is published in the TRANSACTIONS. IEEE currently offers the discounted rate of US$1750 per article. The traditional option, if selected, enables access to all qualified subscribers and purchasers via IEEE Xplore. For the traditional option, no OA payment is required. The IEEE peer review standard of excellence is applied consistently to all submissions. All accepted articles will be included in the print issuemailed to subscribers.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Second Annual IEEE ICDL and EpiRob 2012: Conference Summary and Report
- Authors: Movellan; J.;Schlesinger, M.;
  Pages: 2 - 2
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
The Coordinating Role of Language in Real-Time Multimodal Learning of Cooperative Tasks
- Authors: Petit; M.;Lallee, S.;Boucher, J.-D.;Pointeau, G.;Cheminade, P.;Ognibene, D.;Chinellato, E.;Pattacini, U.;Gori, I.;Martinez-Hernandez, U.;Barron-Gonzalez, H.;Inderbitzin, M.;Luvizotto, A.;Vouloutsi, V.;Demiris, Y.;Metta, G.;Dominey, P.F.;
  Pages: 3 - 17
  Abstract: One of the defining characteristics of human cognition is our outstanding capacity to cooperate. A central requirement for cooperation is the ability to establish a “shared plan”-which defines the interlaced actions of the two cooperating agents-in real time, and even to negotiate this shared plan during its execution. In the current research we identify the requirements for cooperation, extending our earlier work in this area. These requirements include the ability to negotiate a shared plan using spoken language, to learn new component actions within that plan, based on visual observation and kinesthetic demonstration, and finally to coordinate all of these functions in real time. We present a cognitive system that implements these requirements, and demonstrate the system's ability to allow a Nao humanoid robot to learn a nontrivial cooperative task in real-time. We further provide a concrete demonstration of how the real-time learning capability can be easily deployed on a different platform, in this case the iCub humanoid. The results are considered in the context of how the development of language in the human infant provides a powerful lever in the development of cooperative plans from lower-level sensorimotor capabilities.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
A Survey of the Ontogeny of Tool Use: From Sensorimotor Experience to Planning
- Authors: Guerin; F.;Kruger, N.;Kraft, D.;
  Pages: 18 - 45
  Abstract: In this paper, we review current knowledge on tool use development in infants in order to provide relevant information to cognitive developmental roboticists seeking to design artificial systems that develop tool use abilities. This information covers: 1) sketching developmental pathways leading to tool use competences; 2) the characterization of learning and test situations; 3) the crystallization of seven mechanisms underlying the developmental process; and 4) the formulation of a number of challenges and recommendations for designing artificial systems that exhibit tool use abilities in complex contexts.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Learning Information Acquisition for Multitasking Scenarios in Dynamic Environments
- Authors: Karaoguz; C.;Rodemann, T.;Wrede, B.;Goerick, C.;
  Pages: 46 - 61
  Abstract: Real world environments are so dynamic and unpredictable that a goal-oriented autonomous system performing a set of tasks repeatedly never experiences the same situation even though the task routines are the same. Hence, manually designed solutions to execute such tasks are likely to fail due to such variations. Developmental approaches seek to solve this problem by implementing local learning mechanisms to the systems that can unfold capabilities to achieve a set of tasks through interactions with the environment. However, gathering all the information available in the environment for local learning mechanisms to process is hardly possible due to limited resources of the system. Thus, an information acquisition mechanism is necessary to find task-relevant information sources and applying a strategy to update the knowledge of the system about these sources efficiently in time. A modular systems approach may provide a useful structured and formalized basis for that. In such systems different modules may request access to the constrained system resources to acquire information they are tuned for. We propose a reward-based learning framework that achieves an efficient strategy for distributing the constrained system resources among modules to keep relevant environmental information up to date for higher level task learning and executing mechanisms in the system. We apply the proposed framework to a visual attention problem in a system using the iCub humanoid in simulation.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
A Spike-Based Model of Neuronal Intrinsic Plasticity
- Authors: Chunguang Li;Yuke Li;
  Pages: 62 - 73
  Abstract: The discovery of neuronal intrinsic plasticity (IP) processes which persistently modify a neuron's excitability necessitates a new concept of the neuronal plasticity mechanism and may profoundly influence our ideas on learning and memory. In this paper, we propose a spike-based IP model/adaptation rule for an integrate-and-fire (IF) neuron to model this biological phenomenon. By utilizing spikes denoted by Dirac delta functions rather than computing instantaneous firing rates for the time-dependent stimulus, this simple adaptation rule adjusts two parameters of an individual IF neuron to modify its excitability. As a result, this adaptation rule helps an IF neuron to keep its firing activity in a relatively “low but not too low” level and makes the spike-count distributions computed with adjusted window sizes similar to the experimental results.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Autonomous and Interactive Improvement of Binocular Visual Depth Estimation through Sensorimotor Interaction
- Authors: Mann; T.A.;Yunjung Park;Sungmoon Jeong;Minho Lee;Yoonsuck Choe;
  Pages: 74 - 84
  Abstract: We investigate how a humanoid robot with a randomly initialized binocular vision system can learn to improve judgments about egocentric distances using limited action and interaction that might be available to human infants. First, we show how distance estimation can be improved autonomously. We consider our approach to be autonomous because the robot learns to accurately estimate distance without a human teacher providing the distances to training targets. We find that actions that, in principle, do not alter the robot's distance to the target are a powerful tool for exposing estimation errors. These errors can be used to train a distance estimator. Furthermore, the simple action used (i.e., neck rotation) does not require high level cognitive processing or fine motor skill. Next, we investigate how interaction with humans can further improve visual distance estimates. We find that human interaction can improve distance estimates for far targets outside of the robot's peripersonal space. This is accomplished by extending our autonomous approach above to integrate additional information provided by a human. Together these experiments suggest that both action and interaction are important tools for improving perceptual estimates.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Erratum to "Human-Recognizable Robotic Gestures" [Dec 12 305-314]
- Authors: Cabibihan; J.-J.;So, W.-C.;Pramanik, S.;
  Pages: 85 - 85
  Abstract: In the above-named article [ibid., vol. 4, no. 4, pp. 305-314, Dec. 2012], the current affiliation within the biography of J.-J. Cabibihan was mistakenly written as Gemalto Singapore, Singapore. That is the current affiliation of S. Pramanik. Dr. Cabibihan's current affiliation is the National University of Singapore.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
IEEE Xplore Digital Library
- Pages: 86 - 86
  Abstract: Advertisement: IEEE Xplore digital library. Driving research at the world's leading universities and institutions.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Quality without compromise
- Pages: 87 - 87
  Abstract: Advertisement: Our publications, all peer-reviewed, are consistently the most highly cited in the field. Libraries and IEEE, quality our customers can trust. Journal Citation Report, Institute for Scientific Information, 1991-2001. www.ieee.org.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)
Proven powerful
- Pages: 88 - 88
  Abstract: Advertisement: The IEEE Member Digital Library brings you access to IEEE journals, magazines and conference papers published today or in the last five years. Full-text access to the most essential information in technology today with one convenient subscription. Subscribe: www.ieee.org/ieeemdl.
  PubDate: March 2013
  Issue No: Vol. 5, No. 1 (2013)