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. Ming-Feng Yeh2 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. Ming-Feng Yeh3 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. Ming-Feng Yeh4 CONTENTS Grey System Theory Grey Model / Grey Prediction Grey Relational Analysis Fuzzy Control Fuzzy Logic Fuzzy Control Neural Networks Cerebellar Model Articulation Controller Genetic Algorithm Hybrid Systems Applications

5. Ming-Feng Yeh5 SYLLABUS Textbook Textbook: No textbook. Some references will be assigned in the class. Evaluation Criteria: Midterm Oral Report: 50% Final Oral Report: 50%

6. Ming-Feng Yeh6 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. Ming-Feng Yeh7 Soft Computing MethodologyStrength Neural networkLearning and adaptation Fuzzy set theoryKnowledge representation via fuzzy if-then rule Genetic algorithm and simulated annealing Systematic random search Conventional AISymbolic manipulation

8. Ming-Feng Yeh8 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).