Increasing the Runtime Speed of Case-Based Plan Recognition

Abstract

We present PPC (Plan Projection and Clustering), an algorithm that creates a plan hierarchy for case-based plan recognition systems. PPC is motivated by a desire to improve the response time of robots working in collaboration with humans. It projects the plans of a case base into a Euclidean space and iteratively clusters plans within that space, producing an abstraction hierarchy. Case retrieval traverses down this hierarchy and requires fewer comparisons than a search of the corresponding flat case base. Our approach also has the advantage that it does not require substantial domain knowledge. We report PPC's empirical performance on synthetically generated plans, showing that it increases runtime speed without substantially reducing plan retrieval accuracy when the plans are generated using a non-random distribution.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2015
Accession Number
ADA623036

Entities

People

  • David W. Aha
  • Michael Maynord
  • Swaroop Vattam

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Autonomy
  • Counter WMD

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Automata Theory
  • Classification
  • Clustering
  • Computer Languages
  • Computer Science
  • Computers
  • Engineering
  • Hierarchies
  • Intelligent Agents
  • Intelligent Systems
  • Machine Learning
  • Military Research
  • Natural Language Processing
  • Recognition

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space