Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 11
3327-3332,3364

Intention based reinforcement learning by information maximization

Zhao Tingting
Wu Shuai
Yang Mengnan
Chen Yarui
Wang Yuan
Yang Jucheng
College of Artificial Intelligence, Tianjin University of Science & Technology, Tianjin 300457, China
DOI: 10.19734/j.issn.1001-3695.2022.03.0168

Abstract

Reinforcement learning studies how an agent makes decisions through the interaction with the unknown environment, its core is to learn the policy. The action selection of traditional policy model mainly depends on state perception, historical memory and model parameters, which are difficult to control. However, when human fulfill a task, they usually make decisions according to their own intention or motivation. Inspired by the human decision-making mechanism, in order to make the behavior selection mechanism controllable and enable the agent to choose the action according to the intention, this paper proposed to incorporate the intention variable to the policy model and obtain an intention motivated reinforcement learning method. More specifically, the proposed method maximized the mutual information between the intention variables and the actions, so that the policy could select the action related to the intention variable. Finally, the effectiveness of the proposed intention-motivated control was demonstrated through the complex Mujoco environment in simulated robot control task.

Foundation Support

国家自然科学基金资助项目(61976156)
天津市企业科技特派员项目(20YDTPJC00560)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.03.0168
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 11
Section: Algorithm Research & Explore
Pages: 3327-3332,3364
Serial Number: 1001-3695(2022)11-020-3327-06

Publish History

[2022-06-17] Accepted Paper
[2022-11-05] Printed Article

Cite This Article

赵婷婷, 吴帅, 杨梦楠, 等. 基于互信息最大化的意图强化学习方法的研究 [J]. 计算机应用研究, 2022, 39 (11): 3327-3332,3364. (Zhao Tingting, Wu Shuai, Yang Mengnan, et al. Intention based reinforcement learning by information maximization [J]. Application Research of Computers, 2022, 39 (11): 3327-3332,3364. )

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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