學術產出-Periodical Articles

Article View/Open

Publication Export

Google ScholarTM

政大圖書館

Citation Infomation

  • No doi shows Citation Infomation
題名 Neuroeconomics and agent-based computational economics
作者 Chen, Shu-Heng
陳樹衡
貢獻者 經濟系
關鍵詞 Agent-Based Computational Economics (ACE);Dopaminergic Reward Prediction Hypothesis;Dual System Conjecture;Hyperbolic Discounting;Individual Learning;Methodological Individualism;Multi-Agent System;Neuroeconomics;Modularity
日期 2014-01
上傳時間 24-Nov-2014 15:01:40 (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. 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 anyone 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 paper, the author will start a formal inquiry by focusing on examining the models and parameters used to build software agents.
關聯 International Journal of Applied Behavioral Economics, 3(2), 15-34
資料類型 article
dc.contributor 經濟系en_US
dc.creator (作者) Chen, Shu-Hengen_US
dc.creator (作者) 陳樹衡zh_TW
dc.date (日期) 2014-01en_US
dc.date.accessioned 24-Nov-2014 15:01:40 (UTC+8)-
dc.date.available 24-Nov-2014 15:01:40 (UTC+8)-
dc.date.issued (上傳時間) 24-Nov-2014 15:01:40 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/71631-
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. 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 anyone 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 paper, the author will start a formal inquiry by focusing on examining the models and parameters used to build software agents.en_US
dc.format.extent 159 bytes-
dc.format.mimetype text/html-
dc.language.iso en_US-
dc.relation (關聯) International Journal of Applied Behavioral Economics, 3(2), 15-34en_US
dc.subject (關鍵詞) Agent-Based Computational Economics (ACE);Dopaminergic Reward Prediction Hypothesis;Dual System Conjecture;Hyperbolic Discounting;Individual Learning;Methodological Individualism;Multi-Agent System;Neuroeconomics;Modularityen_US
dc.title (題名) Neuroeconomics and agent-based computational economicsen_US
dc.type (資料類型) articleen