Extending and Applying the EPIC Architecture for Human Cognition and Performance

Abstract

This is the final report for a project on the development and validation of the EPIC cognitive architecture for modeling human cognition and performance. It continued a series of ONRsponsored projects on the development of the EPIC architecture for human cognition and performance, conducted by the same PI and also David Meyer of the University of Michigan. This extended activity produced a large number of products and accomplishments; however, this report documents the outcome of only this specific project. In this project, the EPIC computational architecture for modeling human cognition and performance was extended and applied to tasks especially relevant to military applications. The project took advantage of other Navy-sponsored research on modeling complex tasks by comparing EPIC models to models built with the lower-fidelity but more usable GLEAN architecture for GOMS modeling, and combining the best features of both architectures. This project contributed to the developing capability of human performance modeling to help design future human-machine systems to be maximally effective. In the following section, each specific project goal is stated below, followed by a summary of the work accomplished for that goal.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2011
Accession Number
ADA535789

Entities

People

  • David Kieras

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Aerial Warfare
  • Air Force
  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Cognitive Systems Engineering
  • Computer Programs
  • Computer Science
  • Computers
  • Control Systems
  • Electrical Engineering
  • Human Factors Engineering
  • Human-Robot Interaction
  • Operating Systems
  • Psychology
  • System Software
  • Task Performance And Analysis

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Technical Research and Report Writing.