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155
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ICCAD
1997
IEEE
108views Hardware» more  ICCAD 1997»
15 years 7 months ago
Negative thinking by incremental problem solving: application to unate covering
We introduce a new technique to solve exactly a discrete optimization problem, based on the paradigm of “negative” thinking. The motivation is that when searching the space of...
Evguenii I. Goldberg, Luca P. Carloni, Tiziano Vil...
113
Voted
IJAR
2006
98views more  IJAR 2006»
15 years 3 months ago
A forward-backward Monte Carlo method for solving influence diagrams
Although influence diagrams are powerful tools for representing and solving complex decisionmaking problems, their evaluation may require an enormous computational effort and this...
Andrés Cano, Manuel Gómez, Seraf&iac...
125
Voted
PDCAT
2005
Springer
15 years 9 months ago
A New Algorithm to Solve Synchronous Consensus for Dependent Failures
Fault tolerant algorithms are often designed under the t-out-of-n assumption, which is based on the assumption that all processes or components fail independently with equal proba...
Jun Wang, Min Song
176
Voted
AI
2005
Springer
15 years 3 months ago
MaxSolver: An efficient exact algorithm for (weighted) maximum satisfiability
Maximum Boolean satisfiability (max-SAT) is the optimization counterpart of Boolean satisfiability (SAT), in which a variable assignment is sought to satisfy the maximum number of...
Zhao Xing, Weixiong Zhang
140
Voted
PPSN
2010
Springer
15 years 2 months ago
Design and Comparison of two Evolutionary Approaches for Solving the Rubik's Cube
Solutions calculated by Evolutionary Algorithms have come to surpass exact methods for solving various problems. The Rubik’s Cube multiobjective optimization problem is one such ...
Nail El-Sourani, Markus Borschbach