On-Line Assessment of Expertise

Abstract

The main objective in this report period was to deal with the combinatorial explosion in the size of the belief networks needed to analyze regular problem solving behavior. As mentioned in our proceeding quarterly progress reports, Olae's belief networks can get quite large and intractable with non-toy knowledge bases. We have three approaches for handling this problem: (1) We improved our algorithm that builds a belief net incrementally so that it is only as large as it needs to be for the particular actions we observe the human to make. (2) We tested a well-known Monte Carlo technique (stochastic simulation, Pearl, 1986) for estimating probabilities on the nodes in very large belief networks. (3) We have developed and tested a technique for simplifying complex Bayesian net structures.

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Document Details

Document Type
Technical Report
Publication Date
Jan 07, 1994
Accession Number
ADA274746

Entities

People

  • Joel Martin
  • Kurt VanLehn

Organizations

  • University of Pittsburgh

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Computer Science
  • Explosions
  • Military Research
  • Models
  • Probability
  • Scientists
  • Simulations
  • Students
  • Technical Information Centers
  • Universities

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Artificial Intelligence
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks