Agent-Based Modeling and Behavior Representation (AMBR)
Abstract
This report documents accomplishments and lessons learned in a multi-year project to examine the ability of a range of integrative cognitive modeling architectures to predict human behavior in a common task environment. This Agent-Based Modeling and Behavior Representation (AMBR) project involved a series of human performance model evaluations in which the behavior of computer models could be compared to each other and to actual human operators performing the identical tasks. The first comparison challenged the modelers to build dynamically realistic human cognitive models of multiple task management and attention sharing, by simulating the behavior of an air traffic controller (ATC) operating in a simplified ATC task. The second comparison challenged the modelers to build computational process models that simulated the learning of new concepts in the context of executing the task and to make a priori predictions of human behavior in a transfer condition. This report consists of chanters of a forthcoming book, plus appendices detailing the AMBR methodology.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2004
- Accession Number
- ADA433320
Entities
People
- Brett Benyo
- David E. Diller
- Katherine Godfrey
- Kevin A. Gluck
- Richard W. Pew
- Sachin Date
- Sandra Spector
- Stephen Deutsch
- Yvette J. Tenney
Organizations
- BBN Technologies