Title :
Artificial cognitive BP-CT ant routing algorithm
Author :
Jing, Xu ; Liu, Chunyu ; Sun, Xiaobo
Author_Institution :
Dept. of Autom., Comput. & Control Coll., Harbin Univ. of Sci. & Technol., China
fDate :
31 July-4 Aug. 2005
Abstract :
This paper analyses the primary features of computing intelligence in the circumstance of multi-agents modeling, and the artificial cognitive methods with computing intelligent agents, and the artificial cognitive features in reinforcement learning and the Q-routing algorithm which is a kind of reinforcement learning in the domain of intelligent network. At the same time, aiming at the problem in AntNet routing algorithm, this paper introduces BP-CT ant routing algorithm and simulates the algorithm on OMNeT++ software platform, then proves the availability of the algorithm. Considering the global planning and optimal control theory, BP-CT ant routing algorithm has some potential aspects of intelligent control, and shows good QoS performance.
Keywords :
biology computing; cognitive systems; learning (artificial intelligence); multi-agent systems; OMNeT++ software platform; ant routing algorithm; artificial cognitive methods; global planning; multi-agents modeling; optimal control theory; reinforcement learning; Algorithm design and analysis; Artificial intelligence; Competitive intelligence; Computational modeling; Computer networks; Intelligent agent; Intelligent networks; Learning; Routing; Software algorithms;
Conference_Titel :
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN :
0-7803-9048-2
DOI :
10.1109/IJCNN.2005.1556006
