[robotics-worldwide] Memory and Learning in Robot Cognitive Development (PhD Position proposal)

Giulio Sandini Giulio.Sandini at iit.it
Sun Aug 19 22:54:06 PDT 2012


The Robotics, Brain and Cognitive Sciences Department at  the Fondazione Istituto Italiano di Tecnologia (IIT - www.rbcs.iit.it<http://www.rbcs.iit.it>) is offering positions for the Doctoral Course on "Life and Humanoid Technologies"

http://www.iit.it/en/openings/phd-calls/1595-phd-school-in-life-and-humanoid-technologies.html



If your research interest is in addressing cognition from the human as well as humanoid perspective this proposal may be of interest to you.



At RBCS department top-level neuroscience research and top-level robotics research is being merged to seek answers towards some of the long standing open problems in both fields. The research team at RBCS is composed of neuroscientists, engineers, psychologists, physicists working together to investigate brain functions, realize intelligent machines and advanced prosthesis. RBCS is also the home of the humanoid iCub.

Emphasizing on "cumulative learning/cumulative reasoning" agenda for the cognitive development of iCub, we invite applications/enquiries from prospective candidates interested in investigating computational and biological mechanisms of 'humanlike' memories and endowing humanoid robots (iCub) with similar capabilities (see below for full description of the theme). This PhD project (Theme 1.11, see below) will be partially conducted within the framework of the EU funded project 'DARWIN' (http://darwin-project.eu/) in collaboration with a team of leading international scientists. The state of the art humanoid iCub as well as an industrial platform (see the website) will be used to validate the cognitive architecture in a range of playful scenarios and tasks inspired from animal and infant cognition.



Considering the interdisciplinary nature of the problem, the proposal is open for candidates from diverse disciplines (e.g. physics, biology, robotics, computer science) with an interest in understanding/modeling 'human like' memories and implementing such architectures on cognitive robots.



For further details concerning this research project, please contact: vishwanathan.mohan at iit.it<mailto:vishwanathan.mohan at iit.it>



For more information on administrative issues, please contact:

Ms. Anastasia Bruzzone

Tel. +39 010 71781472

Fax. +39 010 7170817

Email: anastasia.bruzzone at iit.it<mailto:anastasia.bruzzone at iit.it>



To apply, follow the instructions indicated in the links, in short: a detailed CV, a research proposal under one or more themes chosen among those above indicated, reference letters, and any other formal document concerning the degrees earned. Note that these documents are mandatory in order to consider valid the application.



DEADLINE is September 21, 2012 at noon (strict deadline, no extension).

ONLINE APPLICATIONS only, look at:

http://servizionline.unige.it/studenti/post-laurea/dottorato



Theme 1.11: Towards a Humanlike "memory" for Humanoid robots



   Memory is the capability of the nervous system to benefit from experience. For cognitive robots "learning continuously" in time through various playful sensorimotor interactions with the world (and people in it), there is an urgent need to develop an equally powerful (and humanlike) memory architecture that can "abstract and store" useful information in such interactions and remember 'valuable' ones when faced with novel situations. While the neuroscience of memory has progressed significantly in recent times (Patterson et al, 2007, Martin, 2009, Meyer and Damasio, 2009, Squire et al, 2011), computational principles to implement such biologically inspired memory architectures in autonomous robots is still lagging way behind. Certainly, "learning" has been given importance in robotics but most of the learning is still restricted to task specific scenarios (learn to imitate movements, learn to push, learn to stack objects, etc.). Attempts to create a 'task independent' repository of causal knowledge that can be exploited/recycled under different circumstances and goals have been very sparse. This lacuna has to be filled if we are to see the emergence of truly cognitive systems that can use 'experience' to go 'beyond experience' in novel/unencountered situations. Further, we know from several studies in neuroscience that human memories are very different from generic computer memories. It's not a 'warehouse' where information is dumped and retrieved through some iterative search. It is modality independent (ex. You can move from apple to how it tastes, the crunchy sound of it when you bite, and what you can do with it), there is no limit to retrieval (with more experience on a topic you recall more and more). There is a fine categorization between declarative (what is an apple), procedural (how to make an apple pie) and episodic (what you did with an apple yesterday) memory. It is also known that brain networks involved in recalling the past are also active in simulating the future (Schacter et al, 2007, Buckner et al 2007, Buckner et al 2008, Bressler et al, 2010, Sporns, 2010) for reasoning and planning action in novel situations (more recently named as the Default Mode Network of the brain). Considering that cognitive robots envisioned to assist us in the future are being designed to perform their goals in a dynamic and changing world that we humans inhabit, every moment is indeed novel and a powerful humanlike memory grounded in neurobiology is a fundamental requirement to "cognitively" exploit past experience in new situations. This PhD theme invites prospective candidates interested in investigating computational and biological mechanisms of 'humanlike' memories and endowing humanoid robots (iCub) with similar capabilities. This PhD proposal will be conducted within the framework of the EU funded project 'DARWIN' (http://darwin-project.eu/) in collaboration with a team of leading international scientists. The state of the art humanoid iCub as well as an industrial platform (see the website) will be used to validate the cognitive architecture in a range of playful scenarios and tasks inspired from animal and infant cognition.



Suggested References:

[1] Martin A.  Circuits in mind: The neural foundations for object concepts. The Cognitive Neurosciences, 4th Edition.  M. Gazzaniga (Ed.), MIT Press, 1031-1045, 2009.

[2] Patterson, K., Nestor, P.J. & Rogers, T.T. (2007) Where do you know what you know? The representation of semantic knowledge in the human brain, Nature Reviews Neuroscience, 8(12), 976-987 [3] Squire, L.R. & Wixted, J. The cognitive neuroscience of human memory since H.M. Annual Review of Neuroscience,34, 259-288.

[4] Buckner, R.L and Carroll, D.C. (2007) Self-projection and the brain. Trends in Cognitive Science; 2:49-57.

[5]Schacter, D.L., Addis, D.R., and Buckner, R.L. (2007) Remembering the past to imagine the future: the prospective brain. Nat Rev Neurosci; 8(9):657-661.

[6] Bressler SL, Menon V. Large-scale brain networks in cognition: emerging methods and principles. Trends in Cognitive Sciences 14:277-290 (2010).

[7] Sporns,O. "Networks of the Brain", MIT Press, 2010, ISBN 0-262-01469-6.

[8] Meyer K, Damasio A. (2009) Convergence and divergence in a neural architecture for recognition and memory. Trends in Neuroscience. Jul;32(7):376-82.



---
Prof. Giulio Sandini
Head: Robotics, Brain and Cognitive Sciences
Istituto Italiano di Tecnologia
Phone: +39 010 71781 416 - Fax: +39 010 7170817
http://www.rbcs.iit.it


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