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原文連結
論文資訊
- 類型：已發表論文
- 日期：2011
摘要
We review an empirically grounded approach to studying the 湧現 of collective properties from individual interactions in 社會 dynamics. When individual decision-making rules, strategies, can be extracted from the time-series data, these can be used to construct adaptive 社會 circuits. 社會 circuits provide a compact description of collective effects by mapping rules at the individual level to 統計 properties of aggregates. This defines a simple form of 社會 computation. We consider the properties that complexity measures would need to have to best capture regularities at different level of analysis, from individual rules to circuits to 族群 statistics. One obvious benefit of using the properties and structure of 生物 and 社會 systems to guide the development of complexity measures is that it is more likely
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