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原文連結
論文資訊
- 類型：已發表論文
- 日期：2021-07-13
摘要
Bayes' rule is a fundamental principle that has been applied across multiple disciplines. However, few studies have addressed its origin as a 認知 strategy or the underlying basis for generalization from a small sample. Using a simple binary choice model subject to 自然選擇, we derive 貝氏 inference as an adaptive behavior under certain 隨機 environments. Such behavior emerges purely through the forces of 演化, despite the fact that our 族群 consists of mindless individuals without any ability to reason, act strategically, or accurately encode or infer environmental states probabilistically. In addition, three specific environments favor the 湧現 of finite memory-those that are 馬可夫, nonstationary, and environments where sampling contains too little or too much 資訊 about local conditions. These results prov
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