DocumentCode :
2019054
Title :
Efficient per query information extraction from a Hamming oracle
Author :
Ewert, W. ; Montanez, George ; Dembski, W.A. ; Marks, Robert J.
Author_Institution :
Dept. of Comput. Sci., Baylor Univ., Waco, TX, USA
fYear :
2010
fDate :
7-9 March 2010
Firstpage :
290
Lastpage :
297
Abstract :
Computer search often uses an oracle to determine the value of a proposed problem solution. Information is extracted from the oracle using repeated queries. Crafting a search algorithm to most efficiently extract this information is the job of the programmer. In many instances this is done using the programmer´s experience and knowledge of the problem being solved. For the Hamming oracle, we have the ability to assess the performance of various search algorithms using the currency of query count. Of the search procedures considered, blind search performs the worst. We show that evolutionary algorithms, although better than blind search, are a relatively inefficient method of information extraction. An algorithm methodically establishing and tracking the frequency of occurrence of alphabet characters performs even better. We also show that a search for the search for an optimal tree search, as suggested by our previous work, becomes computationally intensive.
Keywords :
evolutionary computation; query formulation; tree searching; Hamming oracle; blind search; computer search; evolutionary algorithm; optimal tree search; per query information extraction; search algorithm; Computer science; Data mining; Evolutionary computation; Frequency; Neural networks; Programming profession; Sampling methods; Software performance; Software standards; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Theory (SSST), 2010 42nd Southeastern Symposium on
Conference_Location :
Tyler, TX
ISSN :
0094-2898
Print_ISBN :
978-1-4244-5690-1
Type :
conf
DOI :
10.1109/SSST.2010.5442816
Filename :
5442816
Link To Document :
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