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A general theory on first passage times with applications to adaptive decision making
Author(s): Xinjia Chen
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Paper Abstract

Modern intelligent systems are expected to be able to learn from experience, making decisions on the basis of the available information and proceeding step by step to a desired goal. An important specification of such adaptive decision making method is the amount of time to accomplish a decision. In this paper, we propose a random walk model for such decision making method. The model involves random processes which have independent stationary increments. The decision times are formulated as first passage times dependent on the parameters of decision rules. Asymptotic and nonasymptotic results are developed for the analysis of first passage times.

Paper Details

Date Published: 13 May 2019
PDF: 14 pages
Proc. SPIE 11021, Unmanned Systems Technology XXI, 110210Q (13 May 2019); doi: 10.1117/12.2517368
Show Author Affiliations
Xinjia Chen, Northwestern State Univ. (United States)


Published in SPIE Proceedings Vol. 11021:
Unmanned Systems Technology XXI
Charles M. Shoemaker; Hoa G. Nguyen; Paul L. Muench, Editor(s)

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