Title :
The learning mechanism design with petri nets for adaptive agent
Author :
Zhou, Qing ; Guo, Xuefeng
Author_Institution :
Sch. of Bus. Adm., Univ. of Pet., Beijing
fDate :
June 30 2008-July 2 2008
Abstract :
The complex adaptive systems (CAS) is a new theory with the goal to study how complex behaviors emerge in systems of relatively simple interacting individuals. The CAS is also a multi-agent system, and learning ability is a crucial characteristic of adaptive agents. This paper explores the learning agent model with Petri nets by considering both the macrostructure and microstructure for complex adaptive systems simulation.
Keywords :
Petri nets; learning systems; multi-agent systems; CAS; Petri nets; adaptive agent; complex adaptive systems; learning mechanism design; multiagent system; Adaptive control; Adaptive systems; Biological cells; Computational modeling; Decision making; Learning systems; Multiagent systems; Petri nets; Programmable control; Supply chains; Classifier system; Complex Adaptive Systems; ECHO Model; Learning Mechanism; Multi-agent system;
Conference_Titel :
Service Systems and Service Management, 2008 International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4244-1671-4
Electronic_ISBN :
978-1-4244-1672-1
DOI :
10.1109/ICSSSM.2008.4598487
