Accession Number:

AD1062083

Title:

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

Descriptive Note:

Technical Report,07 Sep 2017,06 Sep 2018

Corporate Author:

John von Neumann Institute Ho Chi Minh City Vietnam

Personal Author(s):

• Ho, Tu-Bao

Report Date:

2018-10-12

Pagination or Media Count:

45.0

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.

Descriptors:

• clustering
• myocardial ischemia
• artificial neural networks
• supervised machine learning
• probabilistic models
• heart diseases
• cardiovascular system
• machine learning
• disease attributes
• data mining
• pain
• therapy
• autonomous systems

Subject Categories:

• Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE