Expert systems in space: Minimizing crew and ground support with knowledge-based systems at Marshall Space Flight Center

1987 ◽  
Vol 6 (2) ◽  
pp. 18-21 ◽  
Author(s):  
David J. Weeks
Keyword(s):  
Expert Systems ◽  
Space Flight ◽  
Knowledge Based Systems ◽  
Ground Support ◽  
Knowledge Based

INTEGRATING DISTRIBUTED EXPERTISE

1992 ◽  
Vol 01 (03n04) ◽  
pp. 393-410 ◽  
Author(s):  
EVANGELOS SIMOUDIS ◽  
MARK ADLER
Keyword(s):  
Problem Solving ◽  
Expert Systems ◽  
Real World ◽  
Computational Models ◽  
Knowledge Based Systems ◽  
Computing Environment ◽  
The Past ◽  
Knowledge Based ◽  
Narrow Scope ◽  
Distributed Expertise

Over the past ten years a myriad of knowledge-based expert systems have been developed and deployed. These systems have a narrow scope and usually operate in stand-alone mode. They also follow different implementation philosophies and use a variety of reasoning methods. To address problems of wider scope, researchers have developed systems that utilize either centralized or distributed computational models. Each of these systems is homogeneous, and due to the way developed, prohibitively expensive for real-world settings. In this paper we present OMNI, a framework for integrating existing knowledge-based systems in a way that they can cooperate during problem-solving while they remain distributed over a computing environment.

scholarly journals Use of Expert Systems to identify the right strategy to be used in organizations

2019 ◽  
Vol 7 (4) ◽  
pp. 18-20
Author(s):  
Arunava Ghosh
Keyword(s):  
Knowledge Management ◽  
Expert Systems ◽  
Competitive Advantage ◽  
Knowledge Management System ◽  
Knowledge Based Systems ◽  
Single Source ◽  
Knowledge Database ◽  
Knowledge Based ◽  
The Right ◽  
Made In

Expert systems are computer systems that help the computers to make decisions based on a pre-requisite knowledge database. For a competitive advantage, marketing plays an important role. Environment changes needs to be monitored and necessary changes are to be made in an organization. An efficient knowledge management system is required to acquire, store and retrieve the knowledge when needed (Moradi et al., 2013). When these systems acquire knowledge from several sources rather than from a single source, such systems are knowledge-based systems (Luconi et al., 1986).

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