重点介绍机率理论的历史，以及机率理论和因果推理的计算方法。
Emphasizes history of probability theory and computational approaches to probabilistic and causal inference.
机率理论涵盖了人类认知中的许多重要特征，包括感知、推理、信念改变和学习方面。
Probability theory captures a number of essential characteristics of human cognition, including aspects of perception, reasoning, belief revision, and learning.
在这篇论文中，我们将会用机率的理论来了解一个演算法所须要运行的时间。
In this thesis, we will use probability theory to analyze the running time of algorithms.
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