Artificial intelligence CIT 478, Lecture notes of Information Technology

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NATIONAL OPEN UNIVERSITY OF NIGERIA

FACULTY OF SCIENCE

DEPARTMENT OF COMPUTER SCIENCE

COURSE CODE: CIT

COURSE TITLE: ARTIFICIAL INTELLIGENCE

CIT478 COURSE GUIDE

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CIT

ARTIFICIAL INTELLIGENCE

Course Team Dr. J.N. Ndunagu (Developer/Writer) - NOUN Dr. J.N. Ndunagu (Coordinator) - NOUN

COURSE

GUIDE

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National Open University of Nigeria Headquarters 14/16 Ahmadu Bello Way Victoria Island Lagos

Abuja Office No. 5 Dar es Salaam Street Off Aminu Kano Crescent Wuse II, Abuja Nigeria

e-mail: [email protected]

URL: www.nou.edu.ng

Published By: National Open University of Nigeria

First Printed 2012

Reviewed and Reprinted 2021

ISBN: 978-058-826-

All Rights Reserved

CIT478 COURSE GUIDE

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• Introduction… CONTENTS PAGE
• What You Will Learn in This Course…
• Course Aim
• Course Objectives…
• Working through This Course…
  • Course Materials…
  • Study Units…
  • Textbooks and References
  • Assignment File…
  • Presentation Schedule…
• Assessment…
• Tutor Marked Assignments (TMAs)…
• Final Examination and Grading…........................................................
• Course Marking Scheme
• Course Overview…
• How to Get the Most from This Course
• Facilitators/Tutors and Tutorials…

Introduction

Welcome to CIT478 Artificial Intelligence which is a two credit unit course offered in the fourth year to students of the undergraduate degree programme in Communication Technology and Computer Science. There are eleven study Units in this course. There are no prerequisites for studying this course. It has been developed with appropriate local and foreign examples suitable for audience.

This course guide is for distance learners enrolled in the B.Sc. Communication Technology and Computer Science programmes of the National Open University of Nigeria. This guide is one of the several resource tools available to you to help you successfully complete this course and ultimately your programme.

In this guide you will find very useful information about this course, aims and objectives, what the course is about, what course materials you will be used, available services to support your learning, information on assignments and examination. It also offers you guidelines on how to plan your time for study the amount of time you are likely to spend on each study unit as well as your tutor-marked assignments.

I strongly recommend that you go through this course guide and complete the feedback form at the end before you begin studying the course. The feedback form must be submitted to your tutorial facilitator along with your first assignment.

I wish you all the best in your learning experience and successful completion of this course.

What You Will Learn in This Course

The overall aim of this course, CIT478 is to introduce you to artificial Intelligence and the different faculties involved in it. It also examines different ways of approaching AI. It starts with the basics and then moves on to the more advanced concepts. The Search in artificial Intelligence - State Space Search, uninformed Search, informed Search Strategies and tree Search are also treated. You will also learn about Knowledge Representation and programming languages for AI. Finally,

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you will be introduced to Artificial Intelligence and its applications – Expert System and Robotics.

Course Aim

This course aims at introducing you to Artificial Intelligent (AI), different types of intelligent agents (IA) and types of AI search. You are not expected to have experience in Artificial Intelligent before using this course material. It is hoped that the knowledge would help you solve some real world problems.

Course Objectives

In order to achieve this aim, the course has a set of objectives. Each unit has specific objectives which are included at the beginning of the unit. You are expected to read these objectives before you study the unit. You may wish to refer to them during your study to check on your progress. You should always look at the unit objectives after completion of each unit. By doing so, you would have followed the instructions in the unit. Below are the comprehensive objectives of the course as a whole. By meeting these objectives, you should have achieved the aim of the course. Therefore, after going through this course you should be able to:

 State the definition of Artificial Intelligence  List the different faculties involved with intelligent behavior  Explain the different ways of approaching AI  Look at some example systems that use AI  Describe the history of AI  Explain what an agent is and how it interacts with the environment.  Identify the percepts available to the agent and the actions that the agent can execute, if given a problem situation  Measure the performance used to evaluate an agent  State based agents  Identify the characteristics of the environment  Describe the state space representation.  Describe Some algorithms

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To complete this course, you are required to read each study unit, read the textbooks and read other materials which may be provided by the National Open University of Nigeria.

Each unit contains tutor marked assignments and at certain points in the course you would be required to submit assignment for assessment purposes. At the end of the course there is a final examination. The course should take you about a total of eleven (11) weeks to complete. Below is the list of all the components of the course, what you have to do and how you should allocate your time to each unit in order to complete the course on time and successfully.

This course entails that you spend a lot of time to read and practice. For easy understanding of this course, I will advise that you avail yourself the opportunity of attending the tutorials sessions where you would have the opportunity to compare your knowledge with that of other people, and also have your questions answered.

The Course Material

The main components of this course are:

1. The Course Guide
2. Study Units
3. Further Reading/References
4. Assignments
5. Presentation Schedule

Study Units

There are 11 study units and 4 modules in this course. They are:

Module 1 Introduction to AI

Unit 1 What is Artificial Intelligent (AI)? Unit 2 Introduction to Intelligent Agent (IA)

Module 2 Search in Artificial Intelligence

Unit 1 Introduction to State Space Search Unit 2 Uninformed Search

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Unit 3 Informed Search Strategies Unit 4 Tree Search

Module 3 Artificial Intelligence Techniques in Programming and Natural Languages

Unit 1 Knowledge Representation Unit 2 Programming Languages for Artificial Intelligence Unit 3 Natural Language Processing

Module 4 Artificial Intelligence and Its Applications

Unit 1 Expert System Unit 2 Robotics

Textbooks and References

These texts will be of enormous benefit to you in learning this course:

Adrian Walker; Michael McCord; John F. Sowa and Walter G. Wilson (1990). Knowledge Systems and Prolog (Second Edition). Addison-Wesley.

Argumentation in Artificial Intelligence by Iyad Rahwan, Guillermo R. Simari

Arthur B. Markman (1998). Knowledge Representation. Lawrence Erlbaum Associates.

Asimov, Isaac (1996) [1995]. "The Robot Chronicles". Gold. London: Voyager. pp. 224–225. ISBN 0-00-648202-3.

Bates, M. (1995). Models of Natural Language Understanding. Proceedings of the National Academy of Sciences of the United States of America, Vol. 92, No. 22 (Oct. 24, 1995), pp. 9977–

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Jeen Broekstraa, Michel Klein, Stefan Deckerc, Dieter Fenselb, Frank van Harmelenb and Ian Horrocks Enabling knowledge representation on the Web by extending RDF Schema, , April 16

John F. Sowa (2000). Knowledge Representation : Logical, Philosophical, and Computational Foundations. New York: Brooks/Cole.

John McCarthy (1979). History of Lisp "LISP prehistory - Summer 1956 through Summer 1958."

Jose H. (2000). "Beyond the Turing Test". Journal of Logic, Language and Information 9 (4): 447–466. doi:10.1023/A:1008367325700. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.44.

Koenig, Sven; Maxim Likhachev, Yaxin Liu, David Furcy (2004). "Incremental heuristic search in AI". AI Magazine 25 (2): 99–

112. http://portal.acm.org/citation.cfm?id=1017140.

Lowerre, Bruce (1976). "The Harpy Speech Recognition System", Ph.D. thesis, Carnegie Mellon University.

Marakas, George. Decision Support Systems in the 21st Century. Prentice Hall, 1999, p.29.

McCarthy, John (November 12, 2007). "What Is Artificial Intelligence?". http://www-formal.stanford.edu/jmc/whatisai/ whatisai.html

Michael Wooldridge, An Introduction to Multiagent Systems, John Wiley & Sons, Ltd.

Nilsson, N. J. (1980). Principles of Artificial Intelligence. Palo Alto, California: Tioga Publishing Company. ISBN 0-935382-01-1.

Nilsson, Nils (1998). Artificial Intelligence: A New Synthesis , Morgan Kaufmann Publishers, ISBN 978-1-55860-467-4.

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Nishibori; et al. (2003). Robot Hand with Fingers Using Vibration-Type Ultrasonic Motors (Driving Characteristics). Journal of Robotics and Mechatronics. http://www.fujipress.jp/finder/xslt.php?mode= present&inputfile=ROBOT001500060002.xml.

OWL DL Semantics. http://www.obitko.com/tutorials/ontologies- semantic-web/owl-dl-semantics.html.

Park; et al. (2005). Synthetic Personality in Robots and Its Effect on Human-Robot Relationship.

Pearl, Judea (1984). Heuristics: Intelligent Search Strategies for Computer Problem Solving. Addison-Wesley Longman Publishing Co., Inc.. ISBN 0-201-05594-5.

Philippe Martin "Knowledge representation in RDF/XML, KIF, Frame- CG and Formalized-English", , Distributed System Technology Centre, QLD, Australia, July 15-19, 2002

Poole, David; Mackworth, Alan; Goebel, Randy (1998). Computational Intelligence: A Logical Approach. New York: Oxford University Press, ISBN 0195102703, http://www.cs.ubc.ca/spider/poole/ ci.html

Pople H, Heuristic Methods for Imposing Structure on Ill-Structured Problems, in AI in Medicine, Szolovits (ed.). AAAS Symposium 51, Boulder: Westview Press.

Randall Davis, Howard Shrobe, and Peter Szolovits; What Is a Knowledge Representation? AI Magazine, 14(1):17-33,

Ronald Fagin, Joseph Y. Halpern, Yoram Moses, Moshe Y. Vardi Reasoning About Knowledge. MIT Press, 1995, ISBN 0-262- 06162-7.

Ronald J. Brachman, Hector J. Levesque (eds) Readings in Knowledge Representation , Morgan Kaufmann, 1985, ISBN 0-934613-01-X

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Serenko, Alexander; Ruhi, Umar; Cocosila, Mihail (2007). "Unplanned effects of intelligent agents on Internet use: Social Informatics approach". AI and Society 21 (1–2): 141 – 166. doi:10.1007/s00146-006-0051-8. http://foba.lakeheadu.ca/serenko/papers/AI_Society_Serenko_So cial_Impacts_of_Agents.pdf

Shapiro, Stuart C. (1992). "Artificial Intelligence". In Shapiro, Stuart C.. Encyclopedia of Artificial Intelligence (2nd ed.). New York: John Wiley. pp. 54 – 57. ISBN 0471503061. http://www.cse.buffalo.edu/~shapiro/Papers/ai.pdf.

Skillings, J. (2006). "Getting Machines to Think Like Us". cnet. http://news.cnet.com/Getting-machines-to-think-like-us/2008- 11394_3-6090207.html.

Stuart Russell; Peter Norvig (2010). Artificial Intelligence: A Modern Approach (3 ed.). Prentice Hall. ISBN 978-0-13-

Turing, Alan (1950), "Computing Machinery and Intelligence", Mind LIX (236): 433 – 460, doi:10.1093/mind/LIX.236.433, ISSN 0026-4423, http://loebner.net/Prizef/TuringArticle.html.

Yucong Duan, Christophe Cruz (2011). Formalizing Semantic of Natural Language through Conceptualization from Existence. International Journal of Innovation, Management and Technology (2011) 2 (1), pp. 37-42.

Zhou, Rong. Hansen, Eric (2005). "Beam-Stack Search: Integrating Backtracking with Beam Search". http://www.aaai.org/Library/ICAPS/2005/icaps05-010.php

Assignment File

The assignment file will be given to you in due course. In this file, you will find all the details of the work you must submit to your tutor for marking. The marks you obtain for these assignments will count towards the final mark for the course. Altogether, there are 11 tutor marked assignments for this course.

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Presentation Schedule

The presentation schedule included in this course guide provides you with important dates for completion of each tutor marked assignment. You should therefore endeavor to meet the deadlines.

Assessment

There are two aspects to the assessment of this course. First, there are tutor marked assignments; and second, the written examination. Therefore, you are expected to take note of the facts, information and problem solving gathered during the course. The tutor marked assignments must be submitted to your tutor for formal assessment, in accordance to the deadline given. The work submitted will count for 40% of your total course mark. At the end of the course, you will need to sit for a final written examination. This examination will account for 60% of your total score.

Tutor-Marked Assignments (TMAs)

There are 11 TMAs in this course. You need to submit all the TMAs. The best 4 will therefore be counted. When you have completed each assignment, send them to your tutor as soon as possible and make certain that it gets to your tutor on or before the stipulated deadline. If for any reason you cannot complete your assignment on time, contact your tutor before the assignment is due to discuss the possibility of extension. Extension will not be granted after the deadline, unless on extraordinary cases.

Final Examination and Grading

The final examination for CIT478 will be of last for a period of 2 hours and have a value of 60% of the total course grade. The examination will consist of questions which reflect the tutor marked assignments that you have previously encountered. Furthermore, all areas of the course will be examined. It would be better to use the time between finishing the last unit and sitting for the examination, to revise the entire course. You might find it useful to review your TMAs and comment on them before the examination. The final examination covers information from all parts of the course.

Course Marking Scheme

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In distance learning, the study units replace the university lecturer. This is one of the great advantages of distance learning; you can read and work through specially designed study materials at your own pace, and at a time and place that suit you best. Think of it as reading the lecture instead of listening to a lecturer. In the same way that a lecturer might set you some reading to do, the study units tell you when to read your set books or other material. Just as a lecturer might give you an in-class exercise, your study units provide exercises for you to do at appropriate points.

Each of the study units follows a common format. The first item is an introduction to the subject matter of the unit and how a particular unit is integrated with the other units and the course as a whole. Next is a set of learning objectives. These objectives enable you know what you should be able to do by the time you have completed the unit. You should use these objectives to guide your study. When you have finished the units you must go back and check whether you have achieved the objectives. If you make a habit of doing this you will significantly improve your chances of passing the course.

Remember that your tutor‘s job is to assist you. When you need help, don‘t hesitate to call and ask your tutor to provide it.

 Read this Course Guide thoroughly.  Organize a study schedule. Refer to the ‗Course Overview‘ for more details.

Note the time you are expected to spend on each unit and how the assignments relate to the units. Whatever method you chose to use, you should decide on it and write in your own dates for working on each unit.

 Once you have created your own study schedule, do everything you can to stick to it. The major reason that students fail is that they lag behind in their course work.  Turn to Unit 1 and read the introduction and the objectives for the unit.  Assemble the study materials. Information about what you need for a unit is given in the ‗Overview‘ at the beginning of each unit. You will almost always need both the study unit you are working on and one of your set of books on your desk at the same time.

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 Work through the unit. The content of the unit itself has been arranged to provide a sequence for you to follow. As you work through the unit you will be instructed to read sections from your set books or other articles. Use the unit to guide your reading.  Review the objectives for each study unit to confirm that you have achieved them. If you feel unsure about any of the objectives, review the study material or consult your tutor.  When you are confident that you have achieved a unit‘s objectives, you can then start on the next unit. Proceed unit by unit through the course and try to pace your study so that you keep yourself on schedule.  When you have submitted an assignment to your tutor for marking, do not wait for its return before starting on the next unit. Keep to your schedule. When the assignment is returned, pay particular attention to your tutor‘s comments on the tutor-marked assignment form. Consult your tutor as soon as possible if you have any questions or problems.  After completing the last unit, review the course and prepare yourself for the final examination. Check that you have achieved the unit objectives (listed at the beginning of each unit) and the course objectives (listed in this Course Guide ).

Facilitators/Tutors and Tutorials…

There are 11 hours of tutorials provided in support of this course. You will be notified of the dates, times and location of these tutorials, together with the name and phone number of your tutor, as soon as you are allocated a tutorial group.

 Your tutor will mark and comment on your assignments, keep a close watch on your progress and on any difficulties you might encounter and provide assistance to you during the course. You must mail or submit your tutor-marked assignments to your tutor well before the due date (at least two working days are required). They will be marked by your tutor and returned to you as soon as possible.

 Do not hesitate to contact your tutor by telephone, or e-mail if you need help. The following might be circumstances in which you would find help necessary.

Contact your tutor if: