Decision-Theoretic Approach to Plan Recognition

Abstract

In this report, first we give a survey of the work in plan recognition field, including the evolution of different approaches, their strength and weaknesses. Then we propose two decision-theoretic approaches to plan recognition problem, which explicitly take outcome utilities into consideration. One is an extension within the probabilistic reasoning framework, by adding utility nodes to belief nets. The other is based on maximizing the estimated expected utility of possible plan. Illustrative examples are given to explain the approaches. Finally, we compare the two approaches presented in the report and summarize the work.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
AD1170871

Entities

People

  • Jonathan Gratch
  • Wenji Mao

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Cyber
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Bayesian Inference
  • Bayesian Networks
  • Computational Science
  • Computations
  • Computers
  • Grammars
  • Hypotheses
  • Intrusion Detection
  • Intrusion Detection Systems
  • Intrusion Detectors
  • Language
  • Models
  • Natural Language Processing
  • Natural Languages
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Psychology
  • Random Variables
  • Reasoning

Readers

  • Computer Vision.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.