Position-independent near optimal searching and on-line recognition in star polygons

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Abstract

We study the problem of on-line searching for a target inside a polygon. In particular we propose a strategy for finding a target of unknown location in a star polygon with a competitive ratio of 14.5, and we further refine it to 12.72. This makes star polygons the first non-trivial class of polygons known to admit constant competitive searches independent of the position of the target. We also provide a lower bound of 9 for the competitive ratio of searching in a star polygon-which is dose to the upper bound. A similar task consists of the problem of on-line recognition of star polygons for which we also present a strategy with a constant competitive ratio including negative instances.

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López-Ortiz, A., & Schuierer, S. (1997). Position-independent near optimal searching and on-line recognition in star polygons. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1272, pp. 284–296). Springer Verlag. https://doi.org/10.1007/3-540-63307-3_68

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