Development of a Formal Theory of Agent-Based Computing for System Evaluation and System-Design Guidance

Abstract

This report summarizes the research done on the DARPA-sponsored project on the Development of a Formal Theory 0 Agent-Based Computing for System Evaluation and System-Design Guidance, as part of the TASK program. The work was performed between September 2000 and September 2003, at the Artificial Intelligence Laboratory in the Department of Electrical Engineering and Computer Science at the University of Michigan. During the course of the project, significant advances have been made in the area of commitment strategies for autonomous agents, to enable such agents to manage sets of plans with rich temporal constraints in dynamic, uncertain environments. Specifically, we developed a set of computationally efficient techniques for both determining the consistency of sets of actions in order to decide whether or not newly introduced actions are compatible with existing commitments, and for merging new% commitments into sets of existing ones. We also developed strategies for modifying a set of commitments in response to a new, incompatible action. Finally, we applied these computational techniques to various applications of interest to the TASK effort, including e-commerce, a briefing agent", and autonomous unmanned vehicles.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2004
Accession Number
ADA424483

Entities

People

  • Martha E. Pollack

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • C4I

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Alzheimer Disease
  • Artificial Intelligence
  • Brain Injuries
  • Commerce
  • Computer Programming
  • Computer Science
  • Computers
  • Electronic Commerce
  • Engineering
  • Guidance
  • Health Services
  • Information Systems
  • Linear Programming
  • Lisp Programming Language
  • United States
  • Unmanned Vehicles

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Artificial Intelligence
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Autonomous System Control