A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots

Ming Jiang; Li Zhang

doi:10.1109/CIT/IUCC/DASC/PICOM.2015.32

A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots

Ming Jiang, Li Zhang

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Citations (Scopus)

Abstract

This paper introduces and proposes a novel Continuous Learning and Collaborative Decision Making (CLCDM) mechanism to support the real-time cooperation of affective humanoid service robots in smart home/campus environment, in which many highly complicated and intelligence demanding applications, such as homecare and children education are either currently partly assisted or expected to be fully provided in the future by the collaborations of intelligent and affective humanoid robots. The core of the CLCDM approach is a streaming data analytics framework, which incorporates Big Data Analytics facilities and decision making under uncertainty techniques to facilitate the provision of CLCDM capability for affective humanoid service robots to succeed in serving human users needs. An experimental case study is conducted to validate a prototype implementation of the CLCDM approach and the preliminary result demonstrates the feasibility and effectiveness of the promising approach.

Original language	English
Title of host publication	2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	221-225
ISBN (Print)	978-1-5090-0153-8
DOIs	https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.32
Publication status	Published - 26 Oct 2015

Keywords

big data analytics
collaborative decision making
continuous learning
humanoid
real-time cooperation
service robots
streaming data

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10.1109/CIT/IUCC/DASC/PICOM.2015.32

Cite this

Jiang, M., & Zhang, L. (2015). A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots. In 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (pp. 221-225). IEEE. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.32

Jiang, Ming ; Zhang, Li. / A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots. 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. Piscataway, NJ : IEEE, 2015. pp. 221-225

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abstract = "This paper introduces and proposes a novel Continuous Learning and Collaborative Decision Making (CLCDM) mechanism to support the real-time cooperation of affective humanoid service robots in smart home/campus environment, in which many highly complicated and intelligence demanding applications, such as homecare and children education are either currently partly assisted or expected to be fully provided in the future by the collaborations of intelligent and affective humanoid robots. The core of the CLCDM approach is a streaming data analytics framework, which incorporates Big Data Analytics facilities and decision making under uncertainty techniques to facilitate the provision of CLCDM capability for affective humanoid service robots to succeed in serving human users needs. An experimental case study is conducted to validate a prototype implementation of the CLCDM approach and the preliminary result demonstrates the feasibility and effectiveness of the promising approach.",

keywords = "big data analytics, collaborative decision making, continuous learning, humanoid, real-time cooperation, service robots, streaming data",

author = "Ming Jiang and Li Zhang",

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Jiang, M & Zhang, L 2015, A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots. in 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. IEEE, Piscataway, NJ, pp. 221-225. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.32

A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots. / Jiang, Ming; Zhang, Li.
2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. Piscataway, NJ: IEEE, 2015. p. 221-225.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Jiang, Ming

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N2 - This paper introduces and proposes a novel Continuous Learning and Collaborative Decision Making (CLCDM) mechanism to support the real-time cooperation of affective humanoid service robots in smart home/campus environment, in which many highly complicated and intelligence demanding applications, such as homecare and children education are either currently partly assisted or expected to be fully provided in the future by the collaborations of intelligent and affective humanoid robots. The core of the CLCDM approach is a streaming data analytics framework, which incorporates Big Data Analytics facilities and decision making under uncertainty techniques to facilitate the provision of CLCDM capability for affective humanoid service robots to succeed in serving human users needs. An experimental case study is conducted to validate a prototype implementation of the CLCDM approach and the preliminary result demonstrates the feasibility and effectiveness of the promising approach.

AB - This paper introduces and proposes a novel Continuous Learning and Collaborative Decision Making (CLCDM) mechanism to support the real-time cooperation of affective humanoid service robots in smart home/campus environment, in which many highly complicated and intelligence demanding applications, such as homecare and children education are either currently partly assisted or expected to be fully provided in the future by the collaborations of intelligent and affective humanoid robots. The core of the CLCDM approach is a streaming data analytics framework, which incorporates Big Data Analytics facilities and decision making under uncertainty techniques to facilitate the provision of CLCDM capability for affective humanoid service robots to succeed in serving human users needs. An experimental case study is conducted to validate a prototype implementation of the CLCDM approach and the preliminary result demonstrates the feasibility and effectiveness of the promising approach.

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KW - collaborative decision making

KW - continuous learning

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KW - real-time cooperation

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Jiang M, Zhang L. A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots. In 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. Piscataway, NJ: IEEE. 2015. p. 221-225 doi: 10.1109/CIT/IUCC/DASC/PICOM.2015.32

A Novel Continuous Learning and Collaborative Decision Making Mechanism for Real-Time Cooperation of Humanoid Service Robots

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Keywords

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