傳統計算的主要特徵是嚴格、確定和精確，但其並不適合處理現實生活中的許多問題，例如駕駛汽車、下棋、家電控制…等。但軟式計算基於其不確定、不精確及不完全真值的容錯特性，可提供低成本的方案解決許多日常生活中的問題。本課程將介紹軟式計算的基本原理、相關計算模式，及其在人工智慧與機器學習領域的應用。本課程將介紹的軟式計算的計算模式主要包括了: Neural networks、support vector machine、fuzzy logic、evolutionary computation、simulated annealing、swarm intelligence、Bayesian network…等。此外，本課程將搭配相關工具軟體的實際演練，讓學生未來可易於將所學套用在研究與工作上。

The main characteristics of traditional computing are strict, deterministic and precise, but it is not suitable for dealing with many problems in real life, such as driving a car, playing chess, controlling home appliances, etc. However, soft computing can provide low-cost solutions to many problems in daily life based on its fault-tolerant characteristics of uncertainty, imprecision and incomplete truth values. This course will introduce the basic principles of soft computing, related computing models, and its applications in the fields of artificial intelligence and machine learning. The computing models of soft computing that this course will introduce mainly include: Neural networks, support vector machine, fuzzy logic, evolutionary computation, simulated annealing, swarm intelligence, Bayesian network...etc. In addition, this course will be paired with practical exercises on relevant tools and software, so that students can easily apply what they have learned to research and work in the future.

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3. Sebastian Raschka,‎ Vahid Mirjalili, Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition, Packt Publishing Limited., September 20, 2017.
4. Prateek Joshi, Artificial Intelligence with Python, Packt Publishing Limited., January 2017.

1. Su Muchun, Zhang Xiaode, Machine Learning: Neural Networks, Fuzzy Systems and Genetic Algorithm Principles, Fourth Edition, Quanhua Book Co., Ltd., March 2017
2. Li Lianwang, Liao Juezhou, and Xie Zhengxun, Artificial Intelligence: An Introduction to Intelligent Systems, Third Edition, Quanhua Book Co., Ltd., March 2012
3. Sebastian Raschka,‎ Vahid Mirjalili, Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition, Packt Publishing Limited., September 20, 2017.
4. Prateek Joshi, Artificial Intelligence with Python, Packt Publishing Limited., January 2017.