Foundations of Artificial Intelligence

Introduction to the Course

Module G64FAI

General Information

Staff Module Convenor: Dr. Rong Qu (rong.qu@nottingham.ac.uk)

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