Art

J-GLOBAL ID：200902279783413236   Reference number：08A0682411

A Nonlinear Approach to Robust Routing Based on Reinforcement Learning with State Space Compression and Adaptive Basis Construction

状態空間圧縮と適応基底構築を伴う強化学習に基づくロバストルーティングの非線形手法

Author (1)： SATOH Hideki (Future Univ.-Hakodate, Hakodate-shi, JPN)
Material： IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Institute of Electronics, Information and Communication Engineers)  (IEICE Trans Fundam Electron Commun Comput Sci (Inst Electron Inf Commun Eng))
Volume： E91-A  Issue： 7  Page： 1733-1740  Publication year： Jul. 01, 2008 
JST Material Number： F0699C  ISSN： 0916-8508  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： *routing ,  ad hoc network ,  sensor network ,  *reinforcement learning ,  robustness ,  algorithm ,  principal component analysis ,  space ,  interference noise ,  dimensional reduction ,  noise elimination ,  probability ,  locality ,  function approximation ,  multivariate analysis ,  nonlinearity ,  basis function ,  function(mathematics) ,  transmission performance ,  ratio ,  *communication operation
Semi thesaurus term： state space ,  interference cancellation ,  potential function ,  packet loss rate

JST classification (1)： Computer networks  (JC03000K)

Reference (13)：

• KARLOF, C. Secure routing in wireless sensor networks : Attacks and countermeasures. Ac Hoc Networks Journal. 2003, 1, 293-315
• BROCH, J. A performance comparison of multi-hop wireless ad hoc network routing protocols. Proc. 4th Annual ACM/IEEE International Conference on Mobile Computing and Networking, 1998. 1998, 85-97
• HUITEMA, C. Routing in the Internet. 1995
• SUTTON, R. S. Reinforcement Learning. 1998
• BOYAN, J. A. Packet routing in dynamically changing networks : A reinforcement learning approach. Advances in Neural Information Processing Systems. 1993, 6, 671-678

Terms in the title (7)： 状態空間 ,  適応 ,  基底 ,  構築 ,  強化学習 ,  非線形 ,  手法