Connectionists: Final CfP: Advances in Biologically Inspired Reservoir Computing [EXTENDED DEADLINE]

[Simone Scardapane]

[Apologies if you receive multiple copies of this CFP]

--------------------------------------------------------------------------
              Call for papers: Cognitive Computation Special Issue
           ADVANCES IN BIOLOGICALLY INSPIRED RESERVOIR COMPUTING
             Submission deadline [EXTENDED]: 31th October, 2016
http://ispac.diet.uniroma1.it/cognitive-computation-special-issue/
--------------------------------------------------------------------------

Scope and motivations
--------------------------------------------------------------------------
Reservoir computing is a family of techniques for training and analyzing 
recurrent neural networks, wherein the recurrent portion of the network 
is assigned before the training process, typically via stochastic 
assignment of its weights. The non-linear reservoir acts as a 
high-dimensional kernel space, which generates complex dynamics 
characterized by sharp transitions between ordered and chaotic regimes. 
The behavior of this model emulates the functioning of many biological 
(complex) systems, among which the brain.

Driven by the conceptual simplicity of the reservoir and by links with 
neuroscience, computer science and systems’ theory, researchers have 
achieved remarkable breakthroughs, both in theory and in practice. These 
include dynamical models for explaining the working behavior of 
reservoirs, unsupervised strategies for the adaptation of the network, 
and the design of unconventional computing architectures for its execution.

The recent upsurge of interest in fully adaptable recurrent networks, 
far from shifting the attention from the field, has brought renewed 
interest in reservoir computing models. In our era of extreme 
computational power and sophisticated problems, it is essential to 
understand the limits and the potentialities of simple (both 
deterministic and random) collections of processing units. For this 
reason, many fundamental questions remain open, including the design of 
optimal task-dependent reservoirs in a stable fashion, novel 
investigations on the memory and power capabilities of reservoir 
devices, and their applicability in an ever-increasing range of domains.

In light of this, the aim of this special issue is to provide a unified 
platform for bringing forth and advancing the state-of-the-art in 
reservoir computing approaches. Researchers are invited to submit 
innovative works on the theory and implementation of this family of 
techniques, in order to provide an up-to-date overview on the field.

Topics
--------------------------------------------------------------------------
The topics of interest to be covered by this Special Issue include, but 
are not limited to:

     * Theoretical analyses on the computational power of reservoir 
computing.
     * Deep reservoir models.
     * Techniques for the automatic adaptation of the reservoir and the 
readout.
     * Supervised, unsupervised and semi-supervised training criteria.
     * Non-conventional substrates for the implementations of reservoirs.
     * Parallel and distributed algorithms for reservoir computing.
     * Comparisons between reservoir computing and standard (deep) 
neural networks.
     * Reservoir computing for reinforcement learning problems.
     * Fundamental links between reservoir computing and neuroscientific 
findings.
     * Investigation of reservoir dynamic in a phase space of reduced 
dimensionality.

Applicative papers in all areas (including robotics, industrial control, 
etc.) are welcome, as well as outstanding surveys on specific aspects of 
the field.

Paper submission
--------------------------------------------------------------------------
All papers should follow the manuscript preparation requirements for the 
Springer Cognitive Computation submissions, see 
http://www.springer.com/biomed/neuroscience/journal/12559. The authors 
are requested to submit their manuscripts via the online submission 
manuscript system, available at http://www.editorialmanager.com/cogn/. 
During submission, authors should explicitly choose the title of the 
special issue in the Subject line. Should there be any further 
enquiries, please feel free to address them to the lead guest editor: 
Simone Scardapane (simone.scardapane at uniroma1.it)

Important dates
--------------------------------------------------------------------------
     * Paper submission deadline: October 31, 2016 [EXTENDED]
     * First notification of acceptance: November 30, 2016
     * Submission of revised papers: January 15, 2017
     * Final notification to the authors: January 31, 2017
     * Submission of final/camera-ready papers: February 15, 2017
     * Publication of special issue: TBD

Organizers
--------------------------------------------------------------------------
     * Simone Scardapane (Sapienza University of Rome) - 
simone.scardapane at uniroma1.it
     * John B. Butcher (Keele University) - j.b.butcher at keele.ac.uk
     * Filippo M. Bianchi (UiT, Tromsø) - filippo.m.bianchi at uit.no
     * Zeeshan K. Malik (University of Stirling) - zkm at cs.stir.ac.uk