Foundations of Artificial Intelligencepszrq/files/0FAIintro.pdfLuger Artificial intelligence :...
Transcript of Foundations of Artificial Intelligencepszrq/files/0FAIintro.pdfLuger Artificial intelligence :...
Foundations of Artificial Intelligence
Introduction to the Course
Module G64FAI
General Information
Staff Module Convenor: Dr. Rong Qu ([email protected])
Tel : (0115) 8466503
Office: C43, Computer Science
General Information
Objectives • Provide an introduction to the techniques used in
Artificial Intelligence (AI) • Provide an understanding of the theory of a
range of those techniques • Introduce the students to a number of Artificial
Intelligence applications • Show how these systems can be used to solve
practical problems • Allow the students to become familiar with some
Artificial Intelligence software
General Information
Teaching Methods Lectures: Approx. 18-20 hours.
Private Study: Approx. 30 hours.
Lectures on each Thur&Friday 3pm-4pm Business School Building South A24
General Information
Assessment
Exam (100 %) One two hours exam at the end of the semester. Choose FOUR out of 6 questions. Each question allocated roughly 30 minutes.
General Information
General Points
Lectures will consist of mainly AI theory and principles on problem solving, machine learning, AI history and knowledge representation and reasoning, etc. Lectures will often give demonstrations of the topics being lectured. Lectures will often allow students to participate in class.
General Information
G52PAS-Planning
and Search
G53ADS-Automated
Scheduling
G52APT-AI Programming
Techniques
G53CLP-Constraint
Logic Programming
G53DSM-Decision
Support Systems
G53KRR-Knowledge
Representation and
Reasoning
G53DIA-Design
Intelligent Agents
G53ARB-Advanced
Robotics
Internet Information
All of the lecture notes and presentations from the module will be made available at the module web site. Students will need to access the module site frequently to view lecture presentations, resources, etc. Lecture schedule may slightly change during the semester.
Module Web Site
Course Web Site
http://www.cs.nott.ac.uk/~rxq/g64fai.htm
Resources • Lecture slides & notes • Textbooks • Reading list/material • Lecture schedule • Link to exam papers & exam information
Lectures
Introduction to Artificial Intelligence Problem space & search
Blind searches, heuristic searches Modern search methods (local search, genetic algorithms)
Machine learning Neural network techniques & applications Introduction to data mining
Introduction to knowledge based systems Knowledge representation and reasoning Applications of knowledge based systems
Recommended Reading
Negnevitsky Artificial intelligence : a guide to intelligent systems. Addison-Wesley, 2002. Russell and Norvig Artificial intelligence : a modern approach – 2nd Edition, Prentice Hall, 2003. Cawsey and Alison The essence of artificial intelligence. Prentice Hall, 1998. Luger Artificial intelligence : structures and strategies for complex problem solving, 5th ed. Addison-Wesley, 2005. Ginsberg Essentials of Artificial Intelligence, Morgan Kaufmann Publishers Inc., 1991. The library reading list
Recommended Reading
Negnevitsky Artificial intelligence : a guide to intelligent systems. Addison-Wesley, 2002. Good AI textbook Easy to read while in depth
Recommended Reading
Russell and Norvig Artificial intelligence : a modern approach – 2nd Edition, Prentice Hall, 2003. Web site: http://aima.cs.berkeley.edu/
Good introduction to AI Textbook in many courses
Recommended Reading
Cawsey and Alison The essence of artificial intelligence. Prentice Hall, 1998. Light and easy reading Highlights of AI topics
Recommended Reading
Luger Artificial intelligence : structures and strategies for complex problem solving, 5th ed. Addison-Wesley, 2005. Web site: http://www.cs.unm.edu/~luger/ai-final/
Basic introduction Applications & examples