Jody Paul (Logo) Dr. Jody Paul – Education – MSCD Courses
Foundations of Artificial Intelligence
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Course Information

Title: Foundations of Artificial Intelligence
Institution: Metropolitan State College of Denver
Course ID: CS 4120, Section 1
Semester [CRN]: Fall 2011 [55123]
Meeting Times:

Mondays and Wdnesdays, 4:00 PM - 5:50 PM
Location:

Science 1007
Credit Hours: 4
Prerequisites:

CS 3210 or consent of instructor.
Special Note: Due to the infrequency with which CS 4120 (Foundations of Artificial Intelligence) is offered, for Fall 2011 we will make an effort to accommodate varying levels of background and experience. Thus all students interested in Artificial Intelligence who have a good foundation in computer science are encouraged to enroll for Fall 2011. In particular, if you are comfortable with applying programming and discrete math concepts, you need not have completed CS 3210 to participate in the Fall 2011 AI course.
Course Website: http://www.jodypaul.com/cs/ai
Course Support: http://www.jodypaul.com/moodle2/
Instructor: Dr. Jody Paul (schedule & office hours)
E-mail: jody @ cse.mscd.edu
Office: Science 1038 (x68435)
Campus Mail: Campus Box 38

Course Description

This course combines an overview of the theoretical foundations of artificial intelligence (AI) and hands-on experience with the methods, techniques and tools used to build intelligent systems. Due to the vast breadth of the field of AI, a wide range topics are surveyed, including: knowledge representation, machine learning, neural networks, cognitive science, search strategies, resolution theorem proving, expert systems, reasoning under uncertainty, planning, natural language processing, and case-based reasoning.

Class sessions consist primarily of experiential activities, critical analyses, and guided discussions. A significant amount of preparatory reading and research throughout the course is thus required on the part of all participants.

Participants will have the opportunity to develop demonstration prototypes using object-oriented, functional, and logic-based programming paradigms and implemented in programming languages commonly used for AI.

Course Details, Policies, Resources, Schedule of Topics, Assignments

Resources

Required Texts:
Image of Cover - Link to Amazon

Understanding Artificial Intelligence
by the Editors of Scientific American; Sandy Fritz (Compiler)
Warner Books (2002)
ISBN 0446678759
[RECOMMENDED]
A very accessible overview of AI. Probably good to read this book first.

 
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Artificial Intelligence Illuminated
by Ben Coppin
Jones and Bartlett (2004)
ISBN 0763732303
[REQUIRED]
A relatively comprehensive overview of classic AI (except for cognitive aspects).
Image of Cover - Link to Amazon

The Age of Intelligent Machines
by Ray Kurzweil
MIT Press (1992)
ISBN 0262111217
[REQUIRED]
Full text of book online at no cost:
The Age of Intelligent Machines at KurzweilAI.net
Sources of discounted & used copies:
Amazon, Alibris, Half.Com, AbeBooks, BigWords
Photo of Leiber

Can Animals and Machines Be Persons?
by Justin Leiber
Hackett Publishing Company (1985)
ISBN 0872200027
[REQUIRED]
An entertaining, thought provoking and very accessible presentation of deep issues in artificial intelligence and cognitive science. Addresses controversial and ethical issues in the application of AI.
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Dynamic Memory Revisited
by Roger C. Schank
Cambridge University Press (1999)
ISBN 0521633982
[REQUIRED]
A view from the cognitive side of AI. This gives a good foundation for understanding how to model memory and thought. You might never think about thinking the same way again.

 
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Are We Spiritual Machines?
Ray Kurzweil vs. the Critics of Strong A.I.
Discovery Institute (2001)
ISBN 0963865439
[REQUIRED]
Good treatment of criticisms of strong AI and responses to them.


Recommended Reading (not required):
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AI Application Programming, Second Ed.
by M. Tim Jones
Charles River Media (2005)
ISBN 1584504218
[RECOMMENDED]
Practical illustration of AI algorithms with example source-code in C.
Includes CD with source-code.
Image of Cover - Link to Amazon

Practical Artificial Intelligence Programming in Java, 3rd Ed.
by M. Watson
LuLu (2008) [Link to purchase hardcopy at LuLu]
Creative Commons (2008) [Link to download free PDF]
[RECOMMENDED]
Practical illustration of AI algorithms with example source-code in Java.
Image of Cover - Link to Amazon

The Age of Spiritual Machines: When Computers Exceed Human Intelligence
by Ray Kurzweil
Penguin (2000)
ISBN 0140282025
[RECOMMENDED]
Explanation of automated consciousness & post-biological future.

Articles, Technical Reports, Journals & Conference Proceedings
Examples:
    IJCAI   AAAI   ACM SIGART   AI Magazine    AI-CBR
    Artificial Intelligence Bibliographies


Computing Resources:

Note that all course participants receive an e-mail account and Internet access by virtue of being students at MSCD. (See: http://www.mscd.edu) Use of e-mail and the World Wide Web are required for a successful experience in this course.
You are encouraged to make use of electronic mail to contact me often.

Participants will have the opportunity to read and write programs using conventional languages (such as Java and C), functional languages (such as Scheme and Lisp), and Logic-based languages (such as Prolog). You are encouraged to take advantage of the extensive on-line information, tutorials and tools to help support your use of these languages.
Scheme, Lisp & Prolog Info:
  http://www.swiss.ai.mit.edu/projects/scheme/ (Scheme home)
 http://www.scheme.org/ (Scheme links)
 http://www.scheme.com/ (Chez Scheme)
 http://www.plt-scheme.org/software/mzscheme/ (MzScheme)

Defining Description of Scheme (R5RS)
 Lisp As an Alternative to Java, by Erann Gat, 1999 (PDF)
http://openmcl.clozure.com/ (Common Lisp for Linux & MacOS X)
http://sourceforge.net/projects/jlogic/ (JLog - Prolog in Java)
http://sourceforge.net/projects/gprolog/ (GNU Prolog)

Grading Policy:

You are expected to participate in class discussions and in-class exercises and to make in-class presentations. There will be homework assignments that you are required to complete and turn in. Your final course grade is determined by combining scores on the exercises, presentations, and assignments. You are guaranteed a grade no lower than that given by the following conversion of score (percentage of total possible) to letter grade:
  89% < A;  79% < B < 90%; 69% < C < 80%; 59% < D < 70%; F < 60%

N.B.: Participation in class discussions and exercises is mandatory.

You may submit an assignment after its due date for comments and advice, and you are encouraged to do so. However, the score for that assignment will be recorded officially as 0. Likewise, missing an in-class exercise will result in a score of 0 for that exercise. Unforeseeable crises and emergency situations will be dealt with on a case-by-case basis in accordance with MSCD, College, and Departmental policies.

Note that substantial information will be disseminated during class sessions or on course websites that you will be responsible for knowing whether or not you attended the sessions or accessed the website. Note in particular that the textbooks do not provide all of the information necessary to successfully complete the assignments and exercises.

Collaboration

I encourage collaboration and regard it as essential aspect of Computer Science. Collaboration and discussion with fellow students concerning course information, materials, proofreading, concept exploration, and studying for exams is encouraged. You are not expected to learn the course content or work on assignments in a vacuum on your own. However, you must write up your own submission, individually, for every assignment you turn in even if the solution results from a collaborative effort. In your write-up, you must credit the people with whom you worked. If you consult any reference material, please note in your assignment which sources you used for each part. Note that collaboration is not acceptable during any exam unless specifically indicated. Turning in work that is the result of copying, failure to credit your collaborators, lack of citations for references, and attempts at collaboration or copying during exams will be treated as academic dishonesty. All incidents of suspected dishonesty will be reported to the department and the Dean of the college. Consequences may include a grade of 0 on the assignment or exam, a grade of "F" for the course, academic probation, or dismissal from the institution. This is a very serious matter and should not be taken lightly. If you have any uncertainty or concerns, please discuss them with your instructor or advisor.

Official Announcements

Official policies applicable to all courses: http://cs.mscd.edu/metadot/index.pl?iid=2249

MSCD College Catalog: http://www.mscd.edu/academic/catalog/
Official announcements, including Academic Policies and Procedures and Student Rights and Responsibilities

MSCD Academic Calendar: http://www.mscd.edu/academic/acal.htm
Additional official dates and deadlines, including the last dates to withdraw and receive NC (with and without faculty signatures) and holidays

MSCD Student Handbook: http://handbook.mscd.edu/
Important MSCD and Auraria campus policies and procedures for students

 

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