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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;王卓脩
貢獻者 經濟系
日期 2010
上傳時間 29-Jun-2015 18:03:58 (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 agentbased 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. © 2011, IGI Global.
關聯 Multi-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization
資料類型 book/chapter
DOI http://dx.doi.org/10.4018/978-1-60566-898-7.ch003
dc.contributor 經濟系-
dc.creator (作者) Chen, Shu Heng;Wang, Shu G.-
dc.creator (作者) 陳樹衡;王卓脩-
dc.date (日期) 2010-
dc.date.accessioned 29-Jun-2015 18:03:58 (UTC+8)-
dc.date.available 29-Jun-2015 18:03:58 (UTC+8)-
dc.date.issued (上傳時間) 29-Jun-2015 18:03:58 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/76143-
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 agentbased 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. © 2011, IGI Global.-
dc.relation (關聯) Multi-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization-
dc.title (題名) Neuroeconomics: A viewpoint from agent-based computational economics-
dc.type (資料類型) book/chapteren
dc.identifier.doi (DOI) 10.4018/978-1-60566-898-7.ch003-
dc.doi.uri (DOI) http://dx.doi.org/10.4018/978-1-60566-898-7.ch003 en_US