WCCI2008
Workshop
Machine
Learning in Cognitive Networks: Theory, Application, and Future
with WCCI2008, HongKong, June 7, 2008
Abstract
Cognitive
networks has attracted increasing attention as an advanced form of future
networks that is aware of changes in user needs and its environment, adapts its
behaviour to those changes, learns from its adaptations, and exploits knowledge
to improve its future behaviour. The notion of cognition in cognitive networks
implies a number of intelligent tasks including perception, acting and
planning, learning, reasoning, and decision making,
all of which require a robust knowledge representation that facilitates the
sharing and reuse of knowledge. Hence, machine learning and reasoning play a
key role in fuelling and driving the advance of cognitive networks.
This
workshop aims to explore the state-of-the-art application of machine learning
in cognitive networks and discuss the problems and practical issues of learning
in cognitive network applications. This workshop will also serve as a forum to
bring together academic and industrial researchers working in both areas for
discussing recent advances in theory and application of learning techniques for
cognitive networking.
Themes and Topics
A cognitive network is one
that is aware of changes in user needs and its environment, adapts its behavior to those changes, learns from its adaptations, and
exploits knowledge to improve its future behavior.
The notion of cognition in cognitive networks implies a number of intelligent
tasks including perception, acting and planning, learning, reasoning, and
decision making, all of which require a robust knowledge representation that
facilitates the sharing and reuse of knowledge. Hence, machine learning and
reasoning play a key role in fuelling and driving the advance of cognitive
networks.
Recently a set of
enhancements to the original knowledge plane has been proposed for cognitive
networks to provide high-level dynamic cognitive functionality to augment the
existing low-level rule policies that dictate how the network should behave in
certain scenarios. Learning engines have also been proposed to support decision
making for context-aware services and applications. However, challenges remain
in turning these learning models into viable commercial products. There are
also a mix of open issues regarding the implementation of cognition, including
distributed learning, decision fusion and robust decision making, dynamic
adaptation of parameters, iterative numerical algorithms, and complex adaptive
behaviour, among others.
In this
workshop, we will discuss the following non-exhaustive list of topics:
·
theory and
application of learning, reasoning, and adaptive methods in cognitive
networking;
·
hybrid learning
models and techniques that combine neural computational algorithms with
abstraction and reasoning of a priori knowledge
·
advances in
defining and using a common knowledge representation that can support different
types of dissimilar knowledge for data and decision fusion
·
methods and
applications of data fusion, decision fusion, diagnostic analysis for cognitive
network management;
·
application of
different forms of computational intelligence to automate decision making in
cognitive networks
·
application of
information and data models to support machine learning in cognitive networking
·
application of ontologies and semantic reasoning algorithms to support
machine reasoning in cognitive networking
·
embedded/distributed
real-time learning and knowledge processing;
·
implementations
of machine learning techniques in cognitive network solutions and
experience/lessons learned;
·
state-of-the-art survey of machine learning in cognitive
networking.
Workshop
Schedule/Important Dates
Submission deadline: March 28, 2008
Review period: March 28 – April 8,
2008
Notification Date: April 8, 2008
Registration Deadline: April 15, 2008
Final version submission: May 3, 2008
Submissions and
Workshop Proceedings
Papers
are limited to
6 pages including all figures, tables, and references.
Please follow the IEEE Computer Society Press Proceedings Author Guidelines foe
8.5X11 formatting to prepare your papers (ftp://pubftp.computer.org/press/outgoing/proceedings/).
Please send your submissions preferably in PDF format to yanliu@motorola.com
by March 28, 2008.
All
submitted papers will be reviewed by the program committee according to originality,
significance, and relevance. Submissions of this workshop will form the basis
of a special issue on machine learning in cognitive networks in a major Journal
or book on Computational Intelligence, where extended versions of accepted
workshop papers will be published.
Registration
Please
register for the workshop through WCCI website at http://www.wcci2008.org/registration.htm.
The deadline for registration for accepted papers is April 15,
2008.
Program
committee
Dr. Sven van der
Meer, Telecommunication Systems and Software Group, Waterford Institute of
Technology,
Prof. Ekram
Hossain,
Prof Manish Parashar,
Prof. Weidong
Xiang,
Dr. Jianfeng
Wang, Philips Research North America,
Dr. Mícheál
Ó Foghlú, Telecommunication Systems and
Software Group,
Dr. Mikhail Smirnov (
Dr. Onur
Altintas,
Workshop Organizers
Prof. Er Meng Joo, Nanyang
Technological University (NTU),
Prof. John Strassner,
Waterford Institute of Technology,
Dr. Yan Liu,
Autonomics Research, Motorola Labs,