Scalable Multi-objects meta-level coordinated learning in Internet of Things
文献类型：期刊论文
| 作者 | Wang JP(王军平) ; JUNPING WANG
|
| 刊名 | Personal and Ubiquitous Computing
 |
| 出版日期 | 2015-10 |
| 卷号 | 19期号:7页码:1133–1144 |
| 关键词 | Coordinated Multi-objects System Meta-level Control Coordinated Learning |
| 英文摘要 | The coordinated learning is importance of technique for cooperative multi-objects system in large-scale Internet of Things. The coordinated learning has attracted a lot of attention for its applications in Internet of Things. However, the self-adaptive makes the coordinated learning difficult to be used in IoT. This paper proposes multi-objects scalable coordinated learning algorithm based on the maximumpotential loss of coordination. The algorithm defines an interaction measure that allows objects to dynamically estimate the potential utility loss of coordination with any cluster of objects. The interaction mechanism makes each object compute their beneficial coordination set in different situations and makes the best use of their limited communication resource in Internet of Things. As a result of experiments, our algorithm adapts policy learning of object and their coordination network for different context. Finally, the experiments with the smart agriculture data set demonstrate that the proposed scheme is effective and robust. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12231]  |
| 专题 | 精密感知与控制研究中心_人工智能与机器学习 |
| 通讯作者 | JUNPING WANG |
| 作者单位 | Laboratory of Precision Sensing and Control Center, Institute of Automation, Chinese Academy |
| 推荐引用方式 GB/T 7714 | Wang JP,JUNPING WANG. Scalable Multi-objects meta-level coordinated learning in Internet of Things[J]. Personal and Ubiquitous Computing,2015,19(7):1133–1144. |
| APA | Wang JP,&JUNPING WANG.(2015).Scalable Multi-objects meta-level coordinated learning in Internet of Things.Personal and Ubiquitous Computing,19(7),1133–1144. |
| MLA | Wang JP,et al."Scalable Multi-objects meta-level coordinated learning in Internet of Things".Personal and Ubiquitous Computing 19.7(2015):1133–1144. |
入库方式： OAI收割
来源：自动化研究所
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