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.
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.
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, firstname.lastname@example.org
Dr. Gary B. Fogel, Natural Selection, Inc., 6480 Weathers Place, Suite 350, San Diego, CA 92121 USA, email@example.com
Dr. Justin Fidock, Defence Science and Technology, Group Land Vehicles and Systems, Land Division, L81, DST Group, Justin.Fidock@dsto.defence.gov.au