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SAT
2005
Springer
133views Hardware» more  SAT 2005»
15 years 9 months ago
Solving Over-Constrained Problems with SAT Technology
Abstract. We present a new generic problem solving approach for overconstrained problems based on Max-SAT. We first define a clausal form formalism that deals with blocks of clau...
Josep Argelich, Felip Manyà
116
Voted
GECCO
2004
Springer
15 years 9 months ago
Fitness Clouds and Problem Hardness in Genetic Programming
This paper presents an investigation of genetic programming fitness landscapes. We propose a new indicator of problem hardness for tree-based genetic programming, called negative ...
Leonardo Vanneschi, Manuel Clergue, Philippe Colla...
140
Voted
QEST
2008
IEEE
15 years 10 months ago
Symbolic Magnifying Lens Abstraction in Markov Decision Processes
Magnifying Lens Abstraction in Markov Decision Processes ∗ Pritam Roy1 David Parker2 Gethin Norman2 Luca de Alfaro1 Computer Engineering Dept, UC Santa Cruz, Santa Cruz, CA, USA ...
Pritam Roy, David Parker, Gethin Norman, Luca de A...
152
Voted
AAAI
2008
15 years 6 months ago
Clause Learning Can Effectively P-Simulate General Propositional Resolution
Currently, the most effective complete SAT solvers are based on the DPLL algorithm augmented by clause learning. These solvers can handle many real-world problems from application...
Philipp Hertel, Fahiem Bacchus, Toniann Pitassi, A...
192
Voted
CPAIOR
2010
Springer
15 years 1 months ago
Lazy Clause Generation: Combining the Power of SAT and CP (and MIP?) Solving
Finite domain propagation solving, the basis of constraint programming (CP) solvers, allows building very high-level models of problems, and using highly specific inference encapsu...
Peter J. Stuckey