Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/3759
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dc.contributor.authorChen, Junhwaen
dc.date.accessioned2008-09-17T09:36:57Zen
dc.date.available2008-09-17T09:36:57Zen
dc.date.copyright2005en
dc.date.issued2005en
dc.identifier.citationChen, J. (2005). Learning in multi-agent systems. Master’s thesis, Nanyang Technological University, Singapore.en
dc.identifier.urihttps://hdl.handle.net/10356/3759en
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.typeThesisen
dc.contributor.supervisorYang Zhonghuaen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.description.degreeMASTER OF ENGINEERING (EEE)en
dc.identifier.doi10.32657/10356/3759en
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