An Adaptive Planner for Real-Time Uncertain Environments

Abstract

The accomplishments under this contract were: (1) the researchers built an adaptive planning architecture for a complex, real-time task environment and a testbed for its principled analysis, (2) developed a model- based methodological approach and used it to analyze numerous aspects of the Phoenix agent architecture, (3) development of a procedure called failure recovery analysis (FRA), for analyzing execution traces of failure recovery to discover when and how the planner's actions may be causing failures, (4) extending the previous work with envelopes with the development of a simple one- parameter decision rule called a slack time envelope, (5) taking several steps toward a formalizing of the problem of plan execution monitoring, (6) building causal models of AI program behavior using path analysis and (7) expanding the scope of the methodological approach and authoring a textbook on empirical methods for Artificial Intelligence.

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Document Details

Document Type
Technical Report
Publication Date
Dec 29, 1992
Accession Number
ADA268147

Entities

People

  • Paul Cohen

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Cognitive Workload
  • Computational Science
  • Computer Programming
  • Computer Science
  • Data Mining
  • Data Science
  • Debugging
  • Fire Fighting
  • Information Science
  • Lisp Programming Language
  • Network Science
  • Probabilistic Models
  • Statistical Algorithms
  • Surveys

Fields of Study

  • Computer science
  • Engineering

Readers

  • Artificial Intelligence
  • Parallel and Distributed Computing.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference