Artificial intelligence techniques for scheduling Space Shuttle missions
Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and pla
Selection note: Curated because it documents AI-assisted Shuttle mission planning and scheduling, a legacy precursor for bounded resource and operations scheduling.
Evidence boundary: NTRS provides open full text, but this conference paper was screened for curation rather than independently or domain reviewed; inclusion is contextual, not automatic claim evidence.
Stable record
ntrs-19950017335
Topic
ai-autonomy
Type
Conference Paper
Publisher
Legacy CDMS
Authors
Henke, Andrea L.; Stottler, Richard H.
Year
1994
Editorial state
metadata curated editorial draft
Reviewer
GShips Project editorial synthesis
Official link checked
2026-07-25
Source-supplied abstract
Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.
Abstract text has not been adopted as a GShips conclusion.
What would change this record?
A newer or corrected version, a retraction, a verified duplicate, a material topic mismatch, a changed access state, or claim-level review would trigger a dated editorial update.
NTRS provides open full text, but this conference paper was screened for curation rather than independently or domain reviewed; inclusion is contextual, not automatic claim evidence.
Source-supplied titles, abstracts, authors, and dates may require correction against the canonical full text.
What would change this page?
A newer or corrected version, retraction, verified duplicate, material topic mismatch, changed access state, or claim-level assessment would change this record.
People, review, and conflicts
Prepared by
GShips Project
Editorial status
metadata-curated-editorial-draft
Editorial reviewer
GShips Project editorial synthesis
Last editorial review
No editorial-review date recorded
Independent review
pending
Independent reviewer
No independent reviewer assigned
Last independent review
No independent-review date exists
Last content edit
Not recorded separately
Official source or link verified
2026-07-25
Declared conflicts
The maintainer intends to explore a commercial venture based on some GShips work. No entity, outside funding, customer, sponsor, or indexed-organization relationship currently exists.