Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/71631
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dc.contributor經濟系en_US
dc.creatorChen, Shu-Hengen_US
dc.creator陳樹衡zh_TW
dc.date2014-01en_US
dc.date.accessioned2014-11-24T07:01:40Z-
dc.date.available2014-11-24T07:01:40Z-
dc.date.issued2014-11-24T07:01:40Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/71631-
dc.description.abstractRecently, 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.extent159 bytes-
dc.format.mimetypetext/html-
dc.language.isoen_US-
dc.relationInternational Journal of Applied Behavioral Economics, 3(2), 15-34en_US
dc.subjectAgent-Based Computational Economics (ACE);Dopaminergic Reward Prediction Hypothesis;Dual System Conjecture;Hyperbolic Discounting;Individual Learning;Methodological Individualism;Multi-Agent System;Neuroeconomics;Modularityen_US
dc.titleNeuroeconomics and agent-based computational economicsen_US
dc.typearticleen
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.languageiso639-1en_US-
item.openairetypearticle-
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