Abstract : Man-machine cognitive cooperation has become a reality. There are many prototype systems that have demonstrated the capabilities of cognitive cooperation. These systems have artificial cognitive capabilities, thereby allowing teaming with human operators as well as with other artificial cognitive systems. They can actively assist the operator in improving situational awareness and knowing effective actions with respect to the situational context. The most salient feature of these systems is that they have much knowledge in common with the human operator. This enables them to carry out the work tasks on their own, if necessary. Most important, they have explicit knowledge of the prime work system objectives and can cooperate to catch up with the intentions of the team mate, and to interact sensibly as a team mate. Since prototype systems have demonstrated that cognitive cooperation is technically feasible, the following chapters will not dwell on the technical details of artificial cognitive systems. The focus will be on the underlying fundamental ideas about artificial cognitive systems and intrinsic potentials for cognitive cooperation. Hence, this keynote will dwell on the main properties of artificial cognitive systems and how these properties can be used to improve work system capabilities and make work processes more productive and more efficient. It will point out that automation in the new setting of cognitive automation will bring about human-machine cognitive cooperation that is similar to human-human cognitive cooperation, and that it can be exploited for more effective coordination between team-mates, humans as well as machines. (10 figures, 24 refs.)
[1]
Beth Lyall,et al.
Flight deck automation and task management
,
1998,
SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).
[2]
Thomas Prevot,et al.
The cockpit assistant system cassy - design and in-flight evaluation
,
1995
.
[3]
Jens Rasmussen,et al.
Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models
,
1983,
IEEE Transactions on Systems, Man, and Cybernetics.
[4]
Melanie J. Norton.
Expertise and technology, cognition and human‐computer cooperation
,
1996
.
[5]
Stephanie Guerlain,et al.
The Rotorcraft Pilot's Associate Cockpit Information Manager: Acceptable Behavior from a New Crew Member
,
1999
.
[6]
Dipl.-Inform H Putzer,et al.
Cosa – a Generic Approach towards a Cognitive System Architecture
,
.
[7]
K. J. Vicente,et al.
Cognitive Work Analysis: Toward Safe, Productive, and Healthy Computer-Based Work
,
1999
.
[8]
John M. Reising,et al.
The Human-Electronic Crew: The Right Stuff? Proceedings of the 4th Joint GAF/RAF/USAF Workshop on Human-Computer Teamwork
,
1999
.
[9]
E. Parzen.
On Estimation of a Probability Density Function and Mode
,
1962
.
[10]
Reiner Onken,et al.
Pilot ’ s assistant in tactical transport missions-Crew Assistant Military Aircraft CAMA
,
2000
.
[11]
Donald F. Specht,et al.
A general regression neural network
,
1991,
IEEE Trans. Neural Networks.
[12]
Charles E. Billings,et al.
Aviation Automation: The Search for A Human-centered Approach
,
1996
.