Intelligent Agents As Synthetic Role Players In Scenario-Based Training

  • Authors:

  • Azad M. Madni;Carla C. Madni

  • Affiliations:

  • Intelligent Systems Technology, Inc., Los Angeles, CA, USA;Intelligent Systems Technology, Inc., Los Angeles, CA, USA

  • Venue:
  • Journal of Integrated Design & Process Science
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Intelligent agents are increasingly being exploited as synthetic role players (e.g., teammates, coaches, and opponents) in scenario-based training (SBT). However, the introduction of intelligent agents into training applications comes with its share of challenges given the unique requirements of each role. In particular, the required level of intelligence depends on the requirements of a particular role. For example, agents performing as "extras" in a scene require little or no intelligence, whereas an in situ remediation agent requires the ability to diagnose student deficiencies relative to, for example, the school solution and provide appropriate instruction to remedy the deficiencies. To perform some functions, agents require an understanding of the problem domain; for others, they merely need to understand their own tasks. In some cases, agents need the ability to plan, whereas in other cases they merely need the ability to react. A pedagogical agent that typically interacts with the learner stands to benefit from having a human persona (an avatar) and an instructor-like personality. In light of the foregoing, the implementation of these agents for scenario-based training (SBT) can take a variety of forms and vary in their level of sophistication. This paper presents the various roles that intelligent agents can play in SBT to dramatically lower training costs without compromising training effectiveness.