Autonomous Action by Learning Group Action Protocols and Case-Based Reasoning

Abstract

The PI has been successful in their tasks for this research grant. They were able to develop and test a new learning theory and algorithms that can learn recommended sequence of actions for heterogeneous and temporal objects, and tested the new algorithm to create treatment actions for a patient. The method developed is generic enough to be applicable to many autonomous systems with appropriate adaptations. There was 1 conference paper and one submitted journal paper as a direct result of this grant.

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Document Details

Document Type
Technical Report
Publication Date
Oct 12, 2018
Accession Number
AD1062083

Entities

People

  • John Von Neumann
  • Tu-bao Ho

Tags

DTIC Thesaurus Topics

  • Cardiovascular System
  • Data Mining
  • Drug Abuse
  • Health Services
  • Heart Diseases
  • Medical Personnel
  • Myocardial Ischemia
  • Neural Networks
  • Probabilistic Models
  • Respiration Disorders
  • Supervised Machine Learning

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Fluid Dynamics (CFD)
  • Technical Research and Report Writing.

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control