Coordinated machine learning and decision support for situation awareness.

Full Abstract

Domains such as force protection require an effective decision maker to maintain a high level of situation awareness. A system that combines humans with neural networks is a desirable approach. Furthermore, it is advantageous for the calculation engine to operate in three learning modes: supervised for initial training and known updating, reinforcement for online operational improvement, and unsupervised in the absence of all external signaling. An Adaptive Resonance Theory based architecture capable of seamlessly switching among the three types of learning is discussed that can be used to help optimize the decision making of a human operator in such a scenario. This is followed by a situation assessment module.

Author information

Author/s: Brannon, N G (NG); Seiffertt, J E (JE); Draelos, T J (TJ); Wunsch, D C (DC);

Affiliation: Reliability Assessment and Human Systems Integration Department, Sandia National Laboratories, Albuquerque, NM 87185, USA.

Journal and publication information

Publication Type: Journal Article; Review

Journal: Neural networks : the official journal of the International Neural Network Society (Neural Netw), published in United States. (Language: eng)

Reference: 2009-Apr; vol 22 (issue 3) : pp 316-25

Dates: Created 2009/05/19; Completed 2009/08/21;

PMID: 19395234, status: MEDLINE (last retrieval date: 8/21/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

External Links for this article
(including full text providers, if available):

Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.

This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.