Modeling Human Performance: Effects of Personal Traits and Transitory States

Abstract

In a recently published report, Gillis, Hursh, Guest, Sweetman, & Ehrlich (2000) reported the development of a Human Performance Model (HPM) for representing realistic behavior by Computer Generated Forces (CGF) Command Entities (CEs). The model as described by Gillis et al. (2000) includes the effects of experience, stress, sleep, and circadian rhythm on the decision-making performance of CEs, but does not completely describe some over variables (e.g., the effects of intelligence, aggressiveness, and personality type) represented in the implemented version of the model. This report supplements the Gillis et al. (2000) report by flilly documenting the implemented HPM to include the effects of these additional variables. This documentation includes flow charts that show how each variable is calculated and how the model components relate to each other. Separate model flow charts are provided for positive, negative, and neutral personality types, along with the equations for computing all model variables. Model deficiencies are identified and improvements are suggested, including better representation of emotions, and inclusion of attention, situational awareness, learning, and leader goals and expectations. Finally, a conceptual model showing how these parameters interrelate is presented.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2002
Accession Number
ADA405062

Entities

People

  • Bob G. Witmer
  • Christian Jerome
  • Stephen L. Goldberg

Organizations

  • U.S. Army Research Institute for the Behavioral and Social Sciences

Tags

DTIC Thesaurus Topics

  • Army Personnel
  • Circadian Rhythms
  • Computers
  • Deficiencies
  • Human Behavior
  • Human Emotions
  • Learning
  • Mathematical Models
  • Military Research
  • Models
  • Motor Skills
  • Personality
  • Random Variables
  • Situational Awareness
  • Social Sciences
  • Training
  • Warfare

Readers

  • Circadian Sleep-Wake Regulation and Chronobiology
  • Computational Modeling and Simulation
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.