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Liebowitz, Jay

Publications and source records attributed to Liebowitz, Jay.

Generically Used Expert Scheduling System (GUESS): User's Guide Version 1.0

This user's guide contains instructions explaining how to best operate the program GUESS, a generic expert scheduling system. GUESS incorporates several important features for a generic scheduler, including automatic scheduling routines to generate a 'first' schedule for the user, a user interface that includes Gantt charts and enables the human scheduler to manipulate schedules manually, diagnostic report generators, and a variety of scheduling techniques. The current version of GUESS runs on an IBM PC or compatible in the Windows 3.1 or Windows '95 environment.

Liebowitz, Jay↗

A Generic Expert Scheduling System Architecture and Toolkit: GUESS (Generically Used Expert Scheduling System)

Scheduling has become an increasingly important element in today's society and workplace. Within the NASA environment, scheduling is one of the most frequently performed and challenging functions. Towards meeting NASA's scheduling needs, a research version of a generic expert scheduling system architecture and toolkit has been developed. This final report describes the development and testing of GUESS (Generically Used Expert Scheduling System).

Liebowitz, Jay↗

An expert system prototype for aiding in the development of software functional requirements for NASA Goddard's command management system: A case study and lessons learned

At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.

Liebowitz, Jay↗