Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorChen, Junhwaen
dc.identifier.citationChen, J. (2005). Learning in multi-agent systems. Master’s thesis, Nanyang Technological University, Singapore.en
dc.description.abstractIn the recent years, multi-agent systems have gained increasing attention. Such systems can be cooperative or competitive. When designing multi-agent systems, designers are generally not able to tell an agent what to do in advance since it is impossible to predict all the situations an agent may experience. Agents have to learn. Although there are standard learning techniques, they need to be customized for a specific application domain. The main objective of this research is to investigate learning techniques available in a multi-agent setting, understand the cooperative and competitive learning, and develop and apply a new learning technique in a multi- agent area.en
dc.rightsNanyang Technological Universityen
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systemsen
dc.titleLearning in multi-agent systemsen
dc.contributor.supervisorYang Zhonghuaen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.description.degreeMASTER OF ENGINEERING (EEE)en
item.fulltextWith Fulltext-
Appears in Collections:EEE Theses
Files in This Item:
File Description SizeFormat 
EEE-THESES_159.pdf7.58 MBAdobe PDFThumbnail

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.