Computational Intelligence for Human-Machine Systems

Call for Papers

With advancements of intelligent human-machine systems, modern machines, or devices should, therefore, be designed not only to fulfill their basic function but also to collaborate with humans with respect to both body and mind. In the past decades, there were few studies on human-machine collaboration in terms of the mind aspect. It is, therefore, an urgent need to motivate research and development in this aspect.

In respond to this need, there are four fundamental questions facing design and control, which are: (1) how should the machine measure human cues non-intrusively? (2) How should the machine infer human's mind state from these cues? (3) How should the controller manage the machine using the information from both machine states and human mind states? And finally (4) how should the controller assist the human to manage the machine while positively affecting the human both ergonomically and esthetically? The ultimate goal of this proposed special issue is to solicit ideas, concepts, and technologies in computational intelligence and to tackle the foregoing questions, especially questions (3) and (4).

Computational intelligence techniques, such as neural networks, fuzzy logics, and evolutionary computing, have found a broad application domain in many scientific and engineering fields. On one hand, these techniques are potentially very promising to the development of design and control technologies for addressing the aforementioned questions. On the other hand, problems arising from human-machine interaction may offer some new challenge to computational intelligence. Putting together the states of knowledge for human-machine system and computational intelligence may, thus, be a source of new ideas, which will enhance the ultimate goal of this special issue.

We invite potential contributors to this special issue to submit their original research and review articles. Potential topics include, but are not limited to:

• Specific signal processing algorithms for psychophysiological signals based on computational intelligence techniques
• Control methods and algorithms for machine systems with consideration of human mind states
• Intelligent management and decision-making methods for achieving the satisfactory performance of the whole human-machine system
• Human cognitive models
• Methods and algorithms for improving reliability, robustness, and resilience of human-machine systems
• Interesting applications such as the driving system and rehabilitation robot

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/cin/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable:

Lead Guest Editor

• Long Cheng, State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Guest Editors

• Yingzi Lin, Department of Mechanical and Industrial Engineering, College of Engineering, Northeastern University, Boston, MA 02115, USA
• W. J. Chris Zhang, Department of Mechanical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, Canada S7N 5A9
• Anton Nijholt, Department of Computer Science, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands