An A-Prolog Decision Support System for the Space Shuttle
PADL '01 Proceedings of the Third International Symposium on Practical Aspects of Declarative Languages
Encoding Planning Problems in Nonmonotonic Logic Programs
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Manifold answer-set programs and their applications
Logic programming, knowledge representation, and nonmonotonic reasoning
ASP at work: spin-off and applications of the DLV system
Logic programming, knowledge representation, and nonmonotonic reasoning
Combining answer set programming and prolog: the ASP-PROLOG system
Logic programming, knowledge representation, and nonmonotonic reasoning
ASPIDE: integrated development environment for answer set programming
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
Synonymous theories and knowledge representations in answer set programming
Journal of Computer and System Sciences
Towards an integration of answer set and constraint solving
ICLP'05 Proceedings of the 21st international conference on Logic Programming
Answer set programming: language, applications and development tools
RR'13 Proceedings of the 7th international conference on Web Reasoning and Rule Systems
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In this work we show how control knowledge was used to improve planning in the USA-Advisor decision support system for the Space Shuttle. The USA-Advisor is a medium size, real-world planning application for use by NASA flight controllers and contains over a dozen domain dependent and domain independent heuristics. Experimental results are presented here, illustrating how this control knowledge helps improve both the quality of plans as well as overall system performance.