The Robotics, Brain and Cognitive Sciences Department at the Fondazione Istituto Italiano di Tecnologia (IIT -
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@iit.it
For more information on administrative issues, please contact:
Ms. Anastasia Bruzzone
Tel. +39 010 71781472
Fax. +39 010 7170817
Email:
anastasia.bruzzone@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.
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Prof. Giulio Sandini
Head: Robotics, Brain and Cognitive Sciences
Istituto Italiano di Tecnologia
and
LIRA-Lab University of Genova
