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題名 Neuroeconomics: A Viewpoint from Agent-Based Computational Economics
作者 Chen, Shu-Heng ; Wang, Shu G.
陳樹衡
貢獻者 經濟系
日期 2011
上傳時間 15-四月-2014 16:27:56 (UTC+8)
摘要 Recently, the relation between neuroeconomics and agent-based computational economics (ACE) has become an issue concerning the agent-based economics community. Neuroeconomics can interest agent-based economists when they are inquiring for the foundation or the principle of the software-agent design, normally known as agent engineering. It has been shown in many studies that the design of software agents is non-trivial and can determine what will emerge from the bottom. Therefore, it has been quested for rather a period regarding whether we can sensibly design these software agents, including both the choice of software agent models, such as reinforcement learning, and the parameter setting associated with the chosen model, such as risk attitude. In this chapter, we shall start a formal inquiry by focusing on examining the models and parameters used to build software agents.
關聯 Multi-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization, Chapter 3, pp.35-49
EISBN13: 9781605668994
資料類型 book/chapter
dc.contributor 經濟系en_US
dc.creator (作者) Chen, Shu-Heng ; Wang, Shu G.en_US
dc.creator (作者) 陳樹衡zh_TW
dc.date (日期) 2011en_US
dc.date.accessioned 15-四月-2014 16:27:56 (UTC+8)-
dc.date.available 15-四月-2014 16:27:56 (UTC+8)-
dc.date.issued (上傳時間) 15-四月-2014 16:27:56 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/65394-
dc.description.abstract (摘要) Recently, the relation between neuroeconomics and agent-based computational economics (ACE) has become an issue concerning the agent-based economics community. Neuroeconomics can interest agent-based economists when they are inquiring for the foundation or the principle of the software-agent design, normally known as agent engineering. It has been shown in many studies that the design of software agents is non-trivial and can determine what will emerge from the bottom. Therefore, it has been quested for rather a period regarding whether we can sensibly design these software agents, including both the choice of software agent models, such as reinforcement learning, and the parameter setting associated with the chosen model, such as risk attitude. In this chapter, we shall start a formal inquiry by focusing on examining the models and parameters used to build software agents.en_US
dc.language.iso en_US-
dc.relation (關聯) Multi-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization, Chapter 3, pp.35-49en_US
dc.relation (關聯) EISBN13: 9781605668994en_US
dc.title (題名) Neuroeconomics: A Viewpoint from Agent-Based Computational Economicsen_US
dc.type (資料類型) book/chapteren