Intelligent Automated Agents for Flight Training Simulators

Abstract

Training in flight simulators will be more effective if the agents involved in the simulation behave realistically. Accomplishing this requires that the automated agents be under autonomous, intelligent control. We are using the Soar cognitive architecture to implement intelligent agents that behave as much like humans as possible. In order to approximate human behavior, the agents must integrate planning and reaction in real time, adapt to new and unexpected situations, learn with experience, and exhibit the cognitive limitations and strengths of humans. This paper describes two simple tactical flight scenarios and the knowledge required for an agent to complete them. In addition, the paper describes an implemented agent model that performs in limited tactical scenarios on three different flight simulators. Artificial intelligence, Believable agents, Flexible behaviors, Realistic training environments, Soar.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1993
Accession Number
ADA278641

Entities

People

  • John E. Laird
  • Milind Tambe
  • Paul Simon Rosenbloom
  • Randolph M. Jones

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Applied Computer Science
  • Artificial Intelligence
  • Computer Science
  • Environment
  • Expert Systems
  • Flight
  • Flight Paths
  • Flight Training
  • Information Science
  • Intelligent Agents
  • Intelligent Systems
  • Machine Learning
  • Pilots
  • Simulations
  • Simulators
  • Training

Readers

  • Artificial Intelligence
  • Aviation Science / Aeronautics.
  • Educational Psychology

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems