MSc Artificial Intelligence Course

Dr W F B Jones
Room M 1.13

© W F B JONES 1994

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Lecture notes etc.

• Copyright.
• About this course - Course Info + Syllabus.
• Recommended Books.
• Lecture 1 - Introduction + Basics.
• Lecture 2 - Question Answering.
• Lecture 3 - Problems, Problem Spaces and Search.
• Lecture 4 - Problem Decomposition.
• Lecture 5 - Hill Climbing, Simulated Annealing and Best First Search.
• Lecture 6 - Agendas
• Lecture 7 - Means End Analysis, GPS, Constarint Satisfaction
• Lecture 8 - Game Playing: NIM, Automatic Game Playing.
• Lecture 9 - Game Playing: Grundy's Game, Alpha-Beta Pruning.
• Lecture 10 - Game Playing: Kalah, Learning.
• Lecture 11 - Knowledge Representation: Intro and Issues.
• Lecture 12 - Knowledge Representation: Weak Slot and Filler Structures.
• Lecture 13 - Knowledge Representation: Strong Slot and Filler Structures.
• Lecture 14 - SADSAM and STUDENT
• Lecture 15 - SHRDLU.
• Lecture 16 - WASP
• Lecture 17 - Natural Language Understanding.
• Lecture 18 - Expert Systems: MYCIN
• Lecture 19 - Planning.
• Lecture 20 - Non-linear Planning: Blocks World.

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