Cooperative multi-knowledge learning control system for obstacle consideration

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Abstract

A safe and reliable control operation can be difficult due to limitations in operator’s skills. A self-developing control system could help assist or even replaces the operators in providing the required control operations. However, the self-developing control system is lack of flexibility in determining the necessary control option in multiple conditions where a human operator usually prevails by experiences in optimizing priority. Here, a cooperative multi-knowledge learning control system is proposed in providing flexibility for determining priority in control options, within multiple conditions by considering the required self-developing control knowledge in fulfilling these conditions. The results show that the system was able to provide consideration in prioritizing the use of the required control knowledge of the condition assigned.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Multi-knowledge; Learning control; Reinforcement learning
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 26 Apr 2021 08:13
Last Modified: 26 Apr 2021 08:13
URI: http://umpir.ump.edu.my/id/eprint/30441
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