NDLI: A method based on Kolmogorov complexity to improve the efficiency of strategy optimization with limited memory space

Content Provider	IEEE Xplore Digital Library
Author	Qing-Shan Jia Qian-Chuan Zhao Yu-Chi Ho
Copyright Year	2006
Description	Author affiliation: Dept. of Autom., Tsinghua Univ., Beijing (Qing-Shan Jia; Qian-Chuan Zhao; Yu-Chi Ho)
Abstract	The pervasive application of digital computer in control and optimization techniques forces us to consider the constraint of limited memory space when dealing with large scale practical systems. As an example, we consider the famous Witsenhausen counterexample with the new constraint of limited memory space in this paper. The main difficulty is how to sample strategies that can be stored in the given memory space efficiently. The concept of Kolmogorov complexity measures the minimal memory space to store a strategy (i.e., simple strategies), but is incomputable. To overcome this difficulty, we propose a method based on ordered binary decision diagram to sample only simple strategies. Besides the high sampling efficiency which is demonstrated by numerical testing, the proposed sampling method can be easily combined with optimization algorithms and performance evaluation techniques. As an example, we show how to combine ordinal optimization, numerical integration, and the proposed sampling method to solve the Witsenhausen problem with the constraint of limited memory space. We hope this work can shed some insights to computer-based optimization problems with memory space constraint in a more general situation
Sponsorship	American Automatic Control Council IFAC
File Size	398990
File Format	PDF
ISBN	1424402093
e-ISBN	1424402107
DOI	10.1109/ACC.2006.1657194
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Optimization methods Memory management Constraint optimization Sampling methods Application software Computer applications Pervasive computing Digital control Force control Control systems
Content Type	Text
Resource Type	Article

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