I. AIMS AND SCOPE
It has been 55+ years since Licklider published his seminal
paper titled “Man-Machine Symbiosis”. Yet, Licklider’s
argument stands still today as it was standing at that time; a
vision that seems to be plausible in the near future. We
particularly quote from this seminal work: “A
multidisciplinary study group, examining future research and
development problems of the Air Force, estimated that it
would be 1980 before developments in artificial intelligence
make it possible for machines alone to do much thinking or
problem solving of military significance. That would leave,
say, five years to develop man-computer symbiosis and 15
years to use it. The 15 may be 10 or 500, but those years
should be intellectually the most creative and exciting in the
history of mankind.”
Today, as we stand on slightly firmer ground to assert that
the era of Human-Machine Symbiosis has begun, perfection in
that symbiosis still remains distant. On the conceptual level,
more refined concepts of Licklider’s vision have been
established; these include (in a chronological order of their
appearance in the literature): Biocybernetics, Brain Computer
Interfaces, Adaptive Aiding, Adaptive Automation, HumanMachine
Teaming, Augmented Cognition, Cognitive-Cyber
Symbiosis, and Human-Autonomy Teaming. On the
engineering level, most of these concepts have been
implemented in one form or another. The field of Air Traffic
Control has possibly been “the” testbed for almost all of these
concepts; but today, autonomous systems are becoming a
primary testbed for all of these concepts.
The above history has relied on less “intelligence” in the
machine, making the symbiotic relationship more challenging.
The field of Computational Intelligence (CI) is introducing
some game-changing and disruptive technologies with the
potential to create a leap forward in this research area. Deep
learning systems are showing promise in making the machine
smarter and adaptive. Fuzzy systems are offering opportunities
to provide transparency to allow the human to understand
what the machine does. Evolutionary computation techniques
are becoming a classic technology to optimize these systems.
Swarm intelligence is offering the foundations for effective
teaming. Behavioral analytics using CI techniques are leading
the way to synthesize low-level actions by both humans and
machines into high-level meaning. Yet, the literature on this
topic is spread over many scattered papers. This special issue
aims to bring the elite of this literature together.
II. THEMES
The special issue welcomes survey, position, and research
papers on the role of Computational Intelligence for one or
more of the following topics:
CI Algorithms (including hybrid algorithms) for Human
Machine Symbiosis to
- create meaning, understand, represent and model
behavior from interaction data,
- design transparent, self-motivated, cognitive and
trusted AI,
- facilitate natural and effective communication
between humans and machines,
Case studies showcasing the use of CI in HumanMachine
Symbiosis, for example in autonomous systems,
safety critical systems including air traffic control, cyber
operations, cyber-physical systems, and other interesting
applications.
Position papers on the role of CI in architectures for
trusted autonomous systems; augmented cognition
systems; big data analytics for human-machine
symbiosis; cognitive-cyber symbiosis, human-autonomy
teaming and human-robot collaboration; role of
psychophysiological and behavioral data in symbiosis;
trust in human-machine interaction and teams; other
related topics.
III. SUBMISSIONS
Manuscripts should be prepared according to the
“Information for Authors” section of the journal found at
http://cis.ieee.org/ieee-transactions-on-emerging-topics-incomputational-intelligence.html
and submissions should be
done through the journal submission website:
https://mc.manuscriptcentral.com/tetci-ieee, by selecting the
Manuscript Type of “Human-Machine Symbiosis”, and clearly
marking “Special Issue on Human-Machine Symbiosis” as
comments to the Editor-in-Chief.
IV. IMPORTANT DATES
Submission Deadline: 3rd September, 2017
First Decision: 30th October, 2017
Revised Manuscripts: 19th November, 2017
Final Decision: 8th January, 2018
Final Manuscripts: 28th January, 2018
V. GUEST EDITORS
Professor Hussein Abbass, University of New South Wales,
Canberra, Northcott Drive, ACT 2600, Australia,
h.abbass@adfa.edu.au
Dr. Gary B. Fogel, Natural Selection, Inc., 6480 Weathers
Place, Suite 350, San Diego, CA 92121 USA, gfogel@naturalselection.com
Dr. Justin Fidock, Defence Science and Technology, Group
Land Vehicles and Systems, Land Division, L81, DST Group,
Justin.Fidock@dsto.defence.gov.au
No comments:
Post a Comment
Note: only a member of this blog may post a comment.