- ...
\title
^{1}
- We thank people who provided code, help, and
discussion: Greg Badros, Alan Borning, Corin Anderson, Mike Ernst,
Zack Ives, Subbarao Kambhampati, Henry Kautz, Jana Koehler, Tessa
Lau, Denise Pinnel, Rachel Pottinger, Bart Selman, and the blind
reviewers. This research was funded in part by Office of Naval
Research Grant N00014-98-1-0147, by the ARCS foundation Barbara
and Tom Cable fellowship, by National Science Foundation Grants
IRI-9303461 and IIS-9872128, and by a National Science Foundation
Graduate Fellowship.
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- ...
\title
^{2}
- Appeared IJCAI-99. Copyright
©1999, International Joint Conference on Artificial
Intelligence (www.ijcai.org). All rights reserved.
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- ... encodings
^{3}
- Encoding each value as a separate
boolean variable is a simple but unwieldy solution;
bitwise-encodings produce smaller formulae but ones which appear
very hard to solve [Ernst
*et al.*1997].
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- ...
variables
^{4}
- While the assignment to the constraint variables is
optimal according to CASSOWARY's objective function, it is not
guaranteed to be the globally optimal assignment to the real
variables by the same measure; a different assignment to the
propositional variables might provide a better solution. So, the
specific function used is not vital (we use CASSOWARY's default
which minimizes the slack in inequalities).
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- ... variables
^{5}
- This restriction falls in
line with the pure literal elimination rule if we consider the
triggers themselves to be clauses. The trigger
` (load
30)` from Figure 2
would then become the clause
`
(load
30)`, and * MaxLoad* could no longer be purely
positive.
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- ... entries
^{6}
- All three sets of runs use minimal conflict
sets, learning, and backjumping.
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