[robotics-worldwide] [news] Neural plasticity for rich and uncertain robotic information streams. Call for participation to our upcoming Frontiers research topic.

Andrea Soltoggio A.Soltoggio at lboro.ac.uk
Tue Jul 1 07:16:33 PDT 2014


Dear all,

I would like to inform you that the research topic “Neural plasticity for
rich and uncertain information streams”, hosted by Frontiers in
Neurorobotics, has now opened for submission.

Description: Models of adaptation and neural plasticity are often
demonstrated in robotic scenarios with heavily pre-processed and regulated
information streams to provide learning algorithms with appropriate, well
timed, and meaningful data to match the assumptions of learning rules. On
the contrary, natural scenarios are often rich of raw, asynchronous,
overlapping and uncertain inputs and outputs whose relationships and
meaning are progressively acquired, disambiguated, and used for further
learning. Therefore, recent research efforts focus on neural embodied
systems that rely less on well timed and pre-processed inputs, but rather
extract autonomously relationships and features in time and space. In
particular, realistic and more complete models of plasticity must account
for delayed rewards, noisy and ambiguous data, emerging and novel input
features during online learning. Such approaches model the progressive
acquisition of knowledge into neural systems through experience in
environments that may be affected by ambiguities, uncertain signals,
delays, or novel features. This research topic promises to unveil
fundamental properties and dynamics of neural learning system that are
naturally immersed in a rich information flow. We invite papers describing
advances in robotic neural learning systems that model adaptation or
plasticity with a rich and realistic stream of information.

Abstract Submission Deadline: Aug 11, 2014,
Article Submission Deadline: Jan 12, 2015

Topic Editor(s): Andrea Soltoggio, Fran van der Velde

Frontiers, a Swiss open-access publisher, recently partnered with Nature
Publishing Group to expand its researcher-driven Open Science platform.
Frontiers articles are rigorously peer-reviewed, can be disseminated freely
and are widely read by your colleagues and by the broader scientific and
medical research communities.

The idea behind a research topic is to create an organized, comprehensive
collection of several contributions, as well as a forum for discussion and
debate. Contributions can be articles describing original research,
methods, hypothesis & theory, opinions, etc.

We have created a homepage on the Frontiers website (Frontiers in
Neurorobotics) where all articles will appear after peer-review and where
participants in the topic will be able to hold relevant discussions:
http://www.frontiersin.org/Neurorobotics/researchtopics/Neural_plasticity_for_rich_and/3107
.

Frontiers will also compile an e-book, as soon as all contributing articles
are published, that can be used in classes, be sent to foundations that
fund your research, to journalists and press agencies, or to any number of
other organizations.

As such, a manuscript accepted for publication incurs a publishing fee,
which varies depending on the article type. Research Topic manuscripts
receive a significant discount on publishing fees. Please take a look at
this fee table: http://www.frontiersin.org/about/PublishingFees.

Once published, your articles will remain free to access for all readers,
and will be indexed in PubMed and other academic archives. As an author in
Frontiers, you retain the copyright to your own papers and figures.

Should you choose to participate, please confirm by sending me a quick
email and then your abstract no later than Aug 11, 2014 using the following
link:
http://www.frontiersin.org/Neurorobotics/researchtopics/Neural_plasticity_for_rich_and/3107



With best regards,

Andrea Soltoggio
Guest Associate Editor, Frontiers in Neurorobotics
www.frontiersin.org

Lecturer in Computer Science and Artificial Intelligence
Haslegrave Building, N.2.03
Loughborough University
LE11 3TU
UK


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