Introduction To Artificial Intelligence

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Introduction to Artificial Intelligence1st year undergraduate degrees with AI and/or CS jxb/iai.htmlLecturer: Dr. John A. Bullinaria jxb John A. Bullinaria, 2005

AI at BirminghamAI is the part of CS concerned with designing intelligent computer systems.There are two routes for studying AI at Birmingham:1. Take a joint honours degree including AI (e.g., BSc AI & CS, BSc Maths & AI)2. Take a CS degree and choose AI options (e.g., BSc CS, BEng/MEng CS/SE )Either way, the Introduction to AI module provides the foundations for your futurestudies. It is a prerequisite for many optional AI modules.Even if you do not want to study AI in more detail later, AI techniques are increasinglybeing used in standard software applications, and having a basic grounding in how theywork is now important for all computer scientists.For up-to-date details of which further AI modules are available for each particulardegree programme, refer to the School’s web-site.w1-2

OutlineThis module provides a general introduction to artificial intelligence, its techniques, andmain sub-fields. The principal focus of the module will be on the common underlyingideas, such as knowledge representation, rule based systems, search, and learning. Itwill provide a foundation for further study of specific areas of artificial intelligence.AimsThe aims of this module are to:1. Provide a general introduction to AI, its techniques and its main sub-fields.2. Give an overview of key underlying ideas, such as knowledge representation, rulebased systems, search, and learning.3. Demonstrate the need for different approaches for different problems4. Provide a foundation for further study of specific areas of AI.w1-3

Learning OutcomesOn completion of this module, the student should be able to:1. Recognise the important features of AI systems and structure the field of AI into itsmain sub-fields.2. Explain some of the most important knowledge representation formalisms and whythey are needed, discussing their advantages and disadvantages. Apply theseknowledge representation formalisms to simple unseen examples.3. Describe and apply some simple search algorithms.4. Outline the processes involved in rule-based Expert Systems and in building suchsystems.5. Discuss the importance of learning in intelligent systems, and how it might beimplemented.6. Provide examples of different types of AI systems, and explain their differences,common techniques, and limitations.w1-4

Syllabus / Lecture PlanWeekSession 1Tuesdays 16:00-17:00Session 2Tuesdays 17:00-18:00Session 3Wednesdays 11:00-12:001Module Organisation––3The Roots, Goals and Sub-fields ofAIBiological Intelligence andNeural Networks4Building Intelligent AgentsExercise Session 35Knowledge RepresentationExercise Session 46Semantic Networks and FramesExercise Session 57Production SystemsExercise Session 68SearchExercise Session 79Expert SystemsExercise Session 810Treatment of UncertaintyExercise Session 911Machine LearningExercise Session 102Exercise Session 1Exercise Session 2Evolutionary Computation(Thorsten Schnier)Neural Network Applications(Peter Tino)Interacting Agent Based Systems(Dean Petters)AI and Philosophy(Aaron Sloman)Natural Language Processing(Mark Lee)Intelligent Robotics(Jeremy Wyatt)Vision(Ela Claridge)Computer Chess(Colin Frayn)AI for Computer Games(Nick Hawes)Machine Learning Applications(Ata Kaban)Colour coding: Black Regular Lecture, Green Exercise Session, Blue Guest Seminar.w1-5

Recommended BooksTitleAuthor(s)Publisher, YearCommentsArtificial Intelligence: AModern ApproachStuart Russell &Peter NorvigPrentice Hall, 2003This is the book that ties in mostclosely with the moduleArtificial Intelligence(2nd ed.)Elaine Rich &Kevin KnightMcGraw Hill, 1991Quite old now, but still a goodsecond bookArtificial Intelligence: A NewSynthesisNils NilssonMorgan Kaufmann, 1998A good modern bookArtificial Intelligence(3rd ed.)Patrick WinstonAddison Wesley, 1992A classic, but not advancedenough nowArtificial IntelligenceMichael NegnevitskyAddison Wesley, 2002A good modern approachArtificial IntelligenceRob CallanPalgrave Macmillan, 2003A good modern bookArtificial Intelligence(5th ed.)George LugerAddison Wesley, 2004Some students may prefer this oneIntroduction to Expert Systems(3rd ed.)Peter JacksonAddison Wesley, 1999The best book on Expert SystemsIf you can only afford to buy one AI book, I would recommend Russell & Norvig.w1-6

Peter Norvig Prentice Hall, 2003 This is the book that ties in most closely with the module Artificial Intelligence (2nd ed.) Elaine Rich & Kevin Knight McGraw Hill, 1991 Quite old now, but still a good second book Artificial Intelligence: A New Synthesis Nils Nilsson Morgan Kaufmann, 1998 A good modern book Artificial Intelligence (3rd ed.) Patrick Winston Addison Wesley, 1992 A classic, but .

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