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» Approximation Algorithms for Domination Search
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167
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GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
15 years 6 months ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
98
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AISB
1994
Springer
15 years 4 months ago
Formal Memetic Algorithms
Abstract. A formal, representation-independent form of a memetic algorithm-a genetic algorithm incorporating local search--is introduced. A generalisedform of N-point crossover is ...
Nicholas J. Radcliffe, Patrick D. Surry
AI
2006
Springer
15 years 17 days ago
Backward-chaining evolutionary algorithms
Starting from some simple observations on a popular selection method in Evolutionary Algorithms (EAs)--tournament selection--we highlight a previously-unknown source of inefficien...
Riccardo Poli, William B. Langdon
73
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AAAI
1998
15 years 1 months ago
Which Search Problems Are Random?
The typical difficulty of various NP-hard problems varies with simple parameters describing their structure. This behavior is largely independent of the search algorithm, but depe...
Tad Hogg
DAM
2008
135views more  DAM 2008»
15 years 18 days ago
Edge ranking and searching in partial orders
: We consider a problem of searching an element in a partially ordered set (poset). The goal is to find a search strategy which minimizes the number of comparisons. Ben-Asher, Farc...
Dariusz Dereniowski