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Representing temporal spatial, and causal knowledge for monitoring and control in an Intelligent Simulation Training System

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1 Author(s)
Interrante, L.D. ; Dept. of Ind. & Syst. Eng., Alabama Univ., Huntsville, AL, USA

The objective of the Intelligent Simulation Training System (ISTS) is to train students in monitoring and controlling physical objects in time and space. The ISTS consists of a graphic computer simulation, an expert system, and a user interface. The expert system must possess a high-level model for reasoning about simulation events. Quantitative simulation data and elicited domain expertise are used to generate an abstract, qualitative model for reasoning purposes. The qualitative model is generated by a subsystem known as ELICIT (Expertise Learner and Intelligent Causal Inference Tool). This paper describes the representations used for generating such a model. ELICIT is implemented in Common LISP and Joshua (a knowledge representation language developed by Symbolics Inc.) on a Symbolics 3630 LISP machine

Published in:
AI, Simulation and Planning in High Autonomy Systems, 1991. Integrating Qualitative and Quantitative System Knowledge, Proceedings of the Second Annual Conference on

Date of Conference: 1-2 Apr 1991

Page(s):
263 - 269
Meeting Date :
01 Apr 1991-02 Apr 1991
Print ISBN:
0-8186-2162-1
INSPEC Accession Number:
4050479
Conference Location :
Cocoa Beach, FL
Digital Object Identifier :
10.1109/AIHAS.1991.138481
Product Type:
Conference Publications

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