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Artificial Intelligence is a Multi-discipline science. It’s developing by penetrating each other include computer science, control theory, information theory, neural physiology, psychology, philology, etc. AI researches how to representing and carrying out human intelligent activity, simulating brain execute reasoning, learning and programming, solving complex problems that only be processed by human, such as image recognition, nature language understanding, evolvement and optimize algorithm. Intelligent principle and system contains classic content and modern agent of AI while it emphasizes on practice system and application. The cores of intelligent principle and system are search algorithms based on symbolic logic, knowledge representation, reasoning and planning, the structure and model, the techniques and methods of intelligent agent. Main teaching contents include: (1) State space representation, blindness search, heuristic search and best-first search in problem-solving. (2) Knowledge and methods of its representation, understanded basic concept and measure of knowledge maintenance, knowledge noise and knowledge discovery. (3) monotony and non-monotony reasoning, resolution principle and forward, backward and bi-deduction in intelligent deduction. (4) theory and methods of planning, machine learning based on examples. (5) design methods and typical applied examples of intelligent agent. This course includes theory teaching and computer experiment that makes students mastering the basic methods of problem-solving and developing ability to intelligent computing and intelligent system
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