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原文連結
論文資訊
- 類型：已發表論文
- 日期：2025-10-01
摘要
Living systems have evolved 認知 complexity to reduce environmental uncertainty, enabling them to predict and prepare for future conditions. Anticipation, distinct from simple prediction, involves active 適應 before an event occurs and is a key feature of both 神經 and a神經 生物 智能體s. Building on the moving average convergence-divergence principle from financial trend analysis, we propose an implementation of anticipation through synthetic biology by designing and evaluating experimentally testable minimal 遺傳 circuits capable of anticipating environmental trends. Through deterministic and 隨機 analyses, we demonstrate that these motifs achieve robust anticipatory responses under a wide range of conditions. Our findings suggest that simple 遺傳 circuits could be naturally exploited by cells to prepare f
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