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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 2
374-378

Probability-based value iteration on optimal state distribution algorithm for POMDP

Zhu Rongxin1,2
Wang Xuan3
Liu Feng3
Zhao Zhihong3,4
1. School of Cyberspace Security, Hainan University, Haikou 570208, China
2. Nanjing Normal University of Special Education, Nanjing 210038, China
3. Software Institute, Nanjing University, Nanjing 210093, China
4. Nanjing Tech University, Nanjing 211816, China
DOI: 10.19734/j.issn.1001-3695.2021.08.0310

Abstract

Point-based value iteration methods are a class of practical algorithms for solving the POMDP model. PBVI is a classical point-based value iteration method with low efficiency. FSVI can reduce the complexity and improve efficiency significantly by using the optimal strategy of the underlying MDP. However, it is not efficient in the large-scale POMDP problems. The paper proposed a probability-based value iteration on optimal state distribution algorithm for POMDP(PBVI-OSD). Du-ring the exploration, PBVI-OSD used the alias method to sample the action a* based on weighted QMDP function and sample the state based on b and the transition function. Then PBVI-OSD selected the observation z whose probability was greater than the threshold, and got the successor point b with great value from a* and z, which ensured the effect of value iteration. Experiment results of four benchmarks show that PBVI-OSD can achieve better global optimal solutions than FSVI and PBVI, especially in large-scale problems.

Foundation Support

国家重点研发计划资助项目(2018YFC1801605)
国家软件新技术重点实验室面上项目(ZZKT2021B08)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.08.0310
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Algorithm Research & Explore
Pages: 374-378
Serial Number: 1001-3695(2022)02-008-0374-05

Publish History

[2021-11-13] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

朱荣鑫, 王譞, 刘峰, 等. 基于环境状态分布优化的POMDP值迭代求解算法 [J]. 计算机应用研究, 2022, 39 (2): 374-378. (Zhu Rongxin, Wang Xuan, Liu Feng, et al. Probability-based value iteration on optimal state distribution algorithm for POMDP [J]. Application Research of Computers, 2022, 39 (2): 374-378. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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