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| Title | Neuroeconomics and agent-based computational economics |
| Creator | Chen, Shu-Heng 陳樹衡 |
| Contributor | 經濟系 |
| Key Words | Agent-Based Computational Economics (ACE);Dopaminergic Reward Prediction Hypothesis;Dual System Conjecture;Hyperbolic Discounting;Individual Learning;Methodological Individualism;Multi-Agent System;Neuroeconomics;Modularity |
| Date | 2014-01 |
| Date Issued | 24-Nov-2014 15:01:40 (UTC+8) |
| Summary | 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. |
| Relation | International Journal of Applied Behavioral Economics, 3(2), 15-34 |
| Type | article |
| dc.contributor | 經濟系 | en_US |
| dc.creator (作者) | Chen, Shu-Heng | en_US |
| dc.creator (作者) | 陳樹衡 | zh_TW |
| dc.date (日期) | 2014-01 | en_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), 15-34 | en_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;Modularity | en_US |
| dc.title (題名) | Neuroeconomics and agent-based computational economics | en_US |
| dc.type (資料類型) | article | en |