Weak Estimator-Based Stochastic Searching on the Line in Dynamic Dual Environments
Document Type
Article
Publication Date
7-1-2022
Abstract
Stochastic point location deals with the problem of finding a target point on a real line through a learning mechanism (LM) with the stochastic environment (SE) offering directional information. The SE can be further categorized into an informative or deceptive one, according to whether ${p}$ is above 0.5 or not, where ${p}$ is the probability of providing a correct suggestion of a direction to LM. Several attempts have been made for LM to work in both types of environments, but none of them considers a dynamically changing environment where ${p}$ varies with time. A dynamic dual environment involves fierce changes that frequently cause its environment to switch from an informative one to a deceptive one, or vice versa. This article presents a novel weak estimator-based adaptive step search solution, to enable LM to track the target in a dynamic dual environment, with the help of a weak estimator. The experimental results show that the proposed solution is feasible and efficient.
Identifier
85107224455 (Scopus)
Publication Title
IEEE Transactions on Cybernetics
External Full Text Location
https://doi.org/10.1109/TCYB.2021.3059939
e-ISSN
21682275
ISSN
21682267
PubMed ID
34033553
First Page
6109
Last Page
6118
Issue
7
Volume
52
Recommended Citation
Zhang, Jun Qi; Qiu, Peng Zhan; Wang, Chun Hui; and Zhou, Meng Chu, "Weak Estimator-Based Stochastic Searching on the Line in Dynamic Dual Environments" (2022). Faculty Publications. 2850.
https://digitalcommons.njit.edu/fac_pubs/2850