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Abstract: This paper addresses two issues: how to choose between solutions for a problem specified by multiple criteria, and how to search for solutions in such situations. We argue against an approach common in decision theory, reducing several criteria to a single `cost' (e.g., using a weighted sum cost function) and instead propose a way of partially ordering solutions satisfying a set of prioritised soft constraints. We describe a generalisation of the A search algorithm which uses this ordering... (Update)
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...see [3, 38] 8. data mining: see [13, 31] 9. graph drawing: see [7, 41] 10. heuristic search in artificial intelligence: see [1, 22, 50, 58]; 11. analysis of linear programming: see [15, 16] 12. transportation: see [18, 20, 21] 13. gene finding: see [32, 39] 14....
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BibTeX entry: (Update)
N. Alechina and B. Logan, State space search with prioritised soft constraints, Applied Intelligence, 14 (2001), 263--272. http://citeseer.ist.psu.edu/alechina01state.html More
@article{ alechina01state,
author = "Natasha Alechina and Brian Logan",
title = "State Space Search with Prioritised Soft Constraints",
journal = "Applied Intelligence",
volume = "14",
number = "3",
pages = "263-272",
year = "2001",
url = "citeseer.ist.psu.edu/alechina01state.html" }
Citations (may not include all citations):311 Partial constraint satisfaction - Freuder, Wallace - 1992
272 Pushing the envelope: Planning - Kautz, Selman - 1996
158 A formal basis for the heuristic determination of minimum co.. (context) - Hart, Nilsson et al. - 1968
27 Possibility theory in constraint satisfaction problems: Hand.. - Dubois, Fargier et al. - 1996
11 A ffl --- an algorithm using search effort estimates (context) - Pearl - 1982
9 Route planning in CCTT (context) - Campbell, Hull et al. - 1995
9 Route planning with ordered constraints - Logan - 1997
7 Least commitment---an optimal planning strategy - Liatsos, Richards - 1997
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