Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/64758
DC FieldValueLanguage
dc.contributor經濟系en_US
dc.creatorChen, Shu-Heng;Tai, C.-C. ; Wang, T.-D. ; Wang, S Gen_US
dc.creator陳樹衡zh_TW
dc.date2011en_US
dc.date.accessioned2014-03-20T09:08:22Z-
dc.date.available2014-03-20T09:08:22Z-
dc.date.issued2014-03-20T09:08:22Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/64758-
dc.description.abstractIn this chapter, we will present agent-based simulations as well as human experiments in double auction markets. Our idea is to investigate the learning capabilities of human traders by studying learning agents constructed by Genetic Programming (GP), and the latter can further serve as a design platform in conducting human experiments. By manipulating the population size of GP traders, we attempt to characterize the innate heterogeneity in human being’s intellectual abilities. We find that GP traders are efficient in the sense that they can beat other trading strategies even with very limited learning capacity. A series of human experiments and multi-agent simulations are conducted and compared for an examination at the end of this chapter.en_US
dc.format.extent184 bytes-
dc.format.mimetypetext/html-
dc.language.isoen_US-
dc.relationMulti-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization, IGI Global, chapter 6, 95-117en_US
dc.titleSocial Simulation with Both Human Agents and Software Agents: An Investigation into the Impact of Cognitive Capacity to Their Learning Behavioren_US
dc.typebook/chapteren
dc.identifier.doi10.4018/978-1-60566-898-7.ch006en_US
dc.doi.urihttp://dx.doi.org/10.4018/978-1-60566-898-7.ch006en_US
item.languageiso639-1en_US-
item.openairetypebook/chapter-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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