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題名: | Agent-based modelling as a foundation for big data | 作者: | Chen, Shu-Heng 陳樹衡 Venkatachalam, Ragupathy |
貢獻者: | 經濟系 | 關鍵詞: | Big data; swarm; prediction markets; information aggregation; agent-based models; abduction | 日期: | 2017 | 上傳時間: | 22-十二月-2018 | 摘要: | In this article, we propose a process-based definition of big data, as opposed to the size- and technology-based definitions. We argue that big data should be perceived as a continuous, unstructured and unprocessed dynamics of primitives, rather than as points (snapshots) or summaries (aggregates) of an underlying phenomenon. Given this, we show that big data can be generated through agent-based models but not by equationbased models. Though statistical and machine learning tools can be used to analyse big data, they do not constitute a big data-generation mechanism. Furthermore, agentbased models can aid in evaluating the quality (interpreted as information aggregation efficiency) of big data. Based on this, we argue that agent-based modelling can serve as a possible foundation for big data. We substantiate this interpretation through some pioneering studies from the 1980s on swarm intelligence and several prototypical agentbased models developed around the 2000s. | 關聯: | JOURNAL OF ECONOMIC METHODOLOGY,24(4), 362-383 | 資料類型: | article | DOI: | http://dx.doi.org/10.1080/1350178X.2017.1388964 |
Appears in Collections: | 期刊論文 |
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