Event Tracking in a Dynamic Multi-Agent Environment.

Abstract

In a dynamic, multi-agent environment, an automated intelligent agent is often faced with the possibility that other agents may instigate events that hinder or help the achievement of its own goals. To act intelligently in such an environment, an automated agent needs an event tracking capability to continually monitor the occurrence of such events and the temporal relationships among them. This capability enables an agent to infer the occurrence of important unobserved events as well as to obtain a better understanding of the interaction among events. This paper focuses on event tracking in one complex and dynamic multi-agent environment: the air-combat simulation environment. It analyzes the challenges that an automated pilot agent must face when tracking events in this environment. This analysis reveals three new issues that have not been addressed in previous work in this area: (1) tracking events generated by agents flexible and reactive behaviors, (2) tracking events in the context of continuous agent interactions, and (3) tracking events in real-time. The paper proposes one solution to address these issues. A key idea in this solution is that the mechanisms that an agent employs in generating its own flexible and reactive behaviors can be used to track other agents flexible and reactive behaviors in real-time. The solution is demonstrated using an implementation of an automated pilot agent.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1994
Accession Number
ADA308468

Entities

People

  • Milind Tambe
  • Paul Simon Rosenbloom

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Air Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Aircrafts
  • Artificial Intelligence
  • Classification
  • Collisions
  • Combat Simulations
  • Computer Science
  • Computers
  • Errors
  • Flight Training
  • Hierarchies
  • Information Science
  • Intelligent Agents
  • Recognition
  • Simulations
  • Students
  • Training

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design

Technology Areas

  • AI & ML