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SOAR: an architecture for general intelligence
Artificial Intelligence
Codes and modalities in multiple resources: a success and a qualification
Human Factors - Special Issue: Human information processing: theory and applications
Unified theories of cognition
Perceptual-motor control in human-computer interaction
Perceptual-motor control in human-computer interaction
Using GOMS for user interface design and evaluation: which technique?
ACM Transactions on Computer-Human Interaction (TOCHI)
The GOMS family of user interface analysis techniques: comparison and contrast
ACM Transactions on Computer-Human Interaction (TOCHI)
ACM Transactions on Computer-Human Interaction (TOCHI)
The Operational Analysis of Queueing Network Models
ACM Computing Surveys (CSUR)
Task Analysis for Human-Computer Interaction
Task Analysis for Human-Computer Interaction
The Psychology of Human-Computer Interaction
The Psychology of Human-Computer Interaction
Computational models of the perceptual, cognitive, and motor processes involved in the visual search of pull-down menus and computer screens
Modeling human performance using the queuing network-model human processor (qn-mhp)
Modeling human performance using the queuing network-model human processor (qn-mhp)
Predictive human performance modeling made easy
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
TYPIST: a theory of performance in skilled typing
Human-Computer Interaction
ACT-R: a theory of higher level cognition and its relation to visual attention
Human-Computer Interaction
Queueing network modeling of human performance of concurrent spatial and verbal tasks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Modeling human interaction resources to support the design of wearable multimodal systems
Proceedings of the 9th international conference on Multimodal interfaces
Queuing Network Modeling of Transcription Typing
ACM Transactions on Computer-Human Interaction (TOCHI)
Rapid prototyping and evaluation of in-vehicle interfaces
ACM Transactions on Computer-Human Interaction (TOCHI)
Bridging the gap: exploring interactions between digital human models and cognitive models
ICDHM'07 Proceedings of the 1st international conference on Digital human modeling
Modeling workload impact in multiple unmanned vehicle supervisory control
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On the architecture of a human-centered CAD agent system
Computer-Aided Design
IEEE Transactions on Intelligent Transportation Systems
Creating personalized digital human models of perception for visual analytics
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Testing & quantifying ERP usability
Proceedings of the 1st Annual conference on Research in information technology
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Queueing Network-Model Human Processor (QN-MHP) is a computational architecture that integrates two complementary approaches to cognitive modeling: the queueing network approach and the symbolic approach (exemplified by the MHP/GOMS family of models, ACT-R, EPIC, and SOAR). Queueing networks are particularly suited for modeling parallel activities and complex structures. Symbolic models have particular strength in generating a person's actions in specific task situations. By integrating the two approaches, QN-MHP offers an architecture for mathematical modeling and real-time generation of concurrent activities in a truly concurrent manner. QN-MHP expands the three discrete serial stages of MHP, of perceptual, cognitive, and motor processing, into three continuous-transmission subnetworks of servers, each performing distinct psychological functions specified with a GOMS-style language. Multitask performance emerges as the behavior of multiple streams of information flowing through a network, with no need to devise complex, task-specific procedures to either interleave production rules into a serial program (ACT-R), or for an executive process to interactively control task processes (EPIC). Using QN-MHP, a driver performance model was created and interfaced with a driving simulator to perform a vehicle steering, and a map reading task concurrently and in real time. The performance data of the model are similar to human subjects performing the same tasks.