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原文連結
論文資訊
- 類型：已發表論文
- 日期：2012
摘要
Animals living in groups collectively produce 社會 structure. In this context individuals make strategic decisions about when to cooperate and compete. This requires that individuals can perceive patterns in collective dynamics, but how this pattern extraction occurs is unclear. Our goal is to identify a model that extracts meaningful 社會 patterns from a behavioral time series while remaining 認知ly parsimonious by making the fewest demands on memory. Using fine-grained conflict data from macaques, we show that sparse coding, an important principle of 神經 compression, is an effective method for compressing 集體行為. The sparse code is shown to be efficient, predictive, and 社會ly meaningful. In our monkey society, the sparse code of conflict is composed of related individuals, the policers, and the al
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