By Scot Anderson, Peter Revesz (auth.), Jean-Daniel Zucker, Lorenza Saitta (eds.)
This publication constitutes the refereed court cases of the sixth overseas Symposium on Abstraction, Reformulation, and Approximation, SARA 2005, held in Airth fort, Scotland, united kingdom in July 2005.
The 17 revised complete papers and eight prolonged abstracts have been rigorously reviewed and chosen for inclusion within the booklet. additionally incorporated are three invited papers and eight examine summaries. All present elements of abstraction, reformulation, and approximation within the context of human commonsense reasoning, challenge fixing, and successfully reasoning in complicated domain names are addressed. one of the software fields of those concepts are automated programming, constraint pride, layout, analysis, computer studying, seek, making plans, reasoning, video game taking part in, scheduling, and theorem proving.
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Additional info for Abstraction, Reformulation and Approximation: 6th International Symposium, SARA 2005, Airth Castle, Scotland, UK, July 26-29, 2005. Proceedings
Dplan is actually a list of sub-plans each solving one task in DT asks . e Dplan = f ail), then GlobalP is reﬁned by substituting every abstract task that appears in DT asks by the portion of the sub-plan that solves it (step 8) (this is a reﬁnement step that iterates over the elements of GlobalP to replace an abstract task related to D by a sub-plan from Dplan if it solves it). The same process repeats with the rest of the domains until ﬁnishing all of them. When all the domains are planned in, the global plan GlobalP is completely reﬁned.
When the level of resource is low, the savings from abstraction are the lowest (less than 15%). The savings are the highest (above 20%) when resource is abundant. A lot of the savings will occur because brunches corresponding to the skip action are suboptimal and therefore will be ignored in a heuristic search but expanded in a “blind” search. In general, the most savings occur when the problem tree has a lot of clearly Generating Admissible Heuristics by Abstraction 25 20 15 10 5 0 25 4000 3000 2000 1000 500 425 350 275 200 125 50 500 425 350 275 200 125 50 0 6000 35 0 25 0 15 4000 2000 5 10 35 20 25 8000 15 30 5 Fig.
Hendler, and D. S. Nau. UMCP: A sound and complete procedure for hierarchical task-network planning. In Artiﬁcial Intelligence Planning Systems, pages 249–254, 1994. 4. E. Fink and Q. Yang. Automatically abstracting the eﬀects of operators. In James Hendler, editor, Proceedings of the 1st International Conference on Artiﬁcial Intelligence Planning Systems (AIPS92), pages 243–251, College Park, Maryland, USA, 1992. Morgan Kaufmann. 5. F. Giunchiglia, A. Villaﬁorita, and T. Walsh. Theories of abstraction.
Abstraction, Reformulation and Approximation: 6th International Symposium, SARA 2005, Airth Castle, Scotland, UK, July 26-29, 2005. Proceedings by Scot Anderson, Peter Revesz (auth.), Jean-Daniel Zucker, Lorenza Saitta (eds.)