Abstract
This paper compares empirically the performance in time and space of two multiobjective graph search algorithms, MOA* and NAMOA*. Previous theoretical work has shown that NAMOA* is never worse than MOA*. Now, a statistical analysis is presented on the relative performance of both algorithms in space and time over sets of randomly generated problems.
This work is partially funded by/Este trabajo está parcialmente financiado por: Consejería de Innovación, Ciencia y Empresa. Junta de Andalucía (España), P07-TIC-03018.
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Machuca, E., Mandow, L., de la Cruz, J.L.P., Ruiz-Sepulveda, A. (2010). An Empirical Comparison of Some Multiobjective Graph Search Algorithms. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., Schultz, T. (eds) KI 2010: Advances in Artificial Intelligence. KI 2010. Lecture Notes in Computer Science(), vol 6359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16111-7_27
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DOI: https://doi.org/10.1007/978-3-642-16111-7_27
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