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Intelligent System

Intelligent System. Ming-Feng Yeh Department of Electrical Engineering Lunghwa University of Science and Technology E-mail: mfyeh@mail.lhu.edu.tw Website: http://mfyeh.myweb.hinet.net Office: F412B-III Tel: #5518. Introduction. What is an “intelligent system”?

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Intelligent System

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  1. Intelligent System Ming-Feng Yeh Department of Electrical Engineering Lunghwa University of Science and Technology E-mail: mfyeh@mail.lhu.edu.tw Website: http://mfyeh.myweb.hinet.net Office: F412B-III Tel: #5518

  2. Introduction • What is an “intelligent system”? • It is hard to define what exactly an “intelligent system” is. • No one can deny that the intelligent system already has an increasing impact on the quality of life in many areas. • Intelligence in a system refers to its ability to learn or adapt, and to modify its functional dependences in response to new experiences or due to changes in the functional relationship.

  3. Introduction • This course will focus on introducing the intelligent system technologies. • The students are expected to learn the basic modeling techniques and to know where to apply the knowledge. • The following materials will be covered in this course:

  4. CONTENTS • Grey System Theory • Grey Model / Grey Prediction • Grey Relational Analysis • Fuzzy Control • Fuzzy Logic • Fuzzy Control • Neural Networks • Neural Networks • Cerebellar Model Articulation Controller • Genetic Algorithm • Hybrid Systems • Applications

  5. SYLLABUS • Textbook: • No textbook. • Some references will be assigned in the class. • Evaluation Criteria: • Midterm Oral Report: 50% • Final Oral Report: 50%

  6. Soft / Hard Computing • Hard computing whose prime desiderata are precision, certainty, and rigor. • Soft computing is tolerant of imprecision, uncertainty, and partial truth. (Lotfi Zadeh) • The primary aim of soft computing is to exploit such tolerance to achieve tractability, robustness, a high level of machine intelligence, and a low cost in practical applications. • Fuzzy logic, neural networks (including CMAC), probabilistic reasoning (genetic algorithm, evolutionary programming, and chaotic systems)

  7. Soft Computing

  8. Computational Intelligence • Fuzzy logic, neural network, genetic algorithm, and evolutionary programming are also considered the building blocks of computational intelligence. (James Bezdek) • Computational intelligence is low-level cognition in the style of human brain and is contrast to conventional (symbolic) artificial intelligence (AI).

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