EPIC (Executive Process-Interactive Control) is a cognitive architecture especially suited for modeling human multimodal and multiple-task performance. The EPIC architecture includes peripheral sensory-motor processors surrounding a production-rule cognitive processor and is being used to construct precise computational models for a variety of human-computer interaction situations. We briefly describe some of these models to demonstrate how EPIC clarifies basic properties of human performance and provides usefully precise accounts of performance speed.

Engineering models of human performance permit some aspects of usability of interface designs to be predicted from an analysis of the task, and thus they can replace to some extent expensive user-testing data. We successfully predicted human performance in telephone operator tasks with engineering models constructed in the EPIC ( E xecutive P rocess- I nteractive C ontrol) architecture for human information processing, which is especially suited for modeling multimodal, complex tasks, and has demonstrated success in other task domains. Several models were constructed on an a priori basis to represent different hypotheses about how operators coordinate their activities to produce rapid task performance. The models predicted the total time with useful accuracy and clarified some important properties of the task. The best model was based directly on the GOMS analysis of the task and made simple assumptions about the operator's task strategy, suggesting that EPIC models are a feasible approach to predicting performance in multimodal high-performance tasks.

Engineering models of human performance permit some aspects of usability of interface designs to be predicted from an analysis of the task, and thus can replace to some extent expensive user testing data. 5/22/13 4:56 PM Predictive Engineering Models Using the EPIC Architecture for a High-Performance Task Page 2 of 10 http://www.sigchi.org/chi95/proceedings/papers/dek_bdy.htm Human performance in telephone operator tasks was successfully predicted using engineering models constructed in the EPIC (Executive Process-Interactive Control) architecture for human informationprocessing, which is especially suited for modeling multimodal, complex tasks. Several models were constructed on an a priori basis to represent different hypotheses about how users coordinate their activities to produce rapid task performance. All of the models predicted the total task time with useful accuracy, and clarified some important properties of the task.