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CS 305 Intro to Artificial Intelligence
Sayles, Kenneth W.


Mission Statement: The mission of Park University, an entrepreneurial institution of learning, is to provide access to academic excellence, which will prepare learners to think critically, communicate effectively and engage in lifelong learning while serving a global community.

Vision Statement: Park University will be a renowned international leader in providing innovative educational opportunities for learners within the global society.

Course

CS 305 Introduction to Artificial Intelligence BL

Semester

S1B 2009 BL

Faculty

Sayles, Kenneth W.

Degrees/Certificates

M.S. Computer Science
CISSP
CEH

Office Hours

By Appointment

Daytime Phone

(915) 217-8214

E-Mail

Kenneth.Sayles@park.edu

Ken.Sayles@gmail.com

Semester Dates

January 10, 2009 to February 28, 2009

Class Days

S

Class Time

1:10 P.M. to 6:10 P.M.

Prerequisites

CS 352 Data Structures

Credit Hours

3


Textbook:
Artificial Intelligence:  A Modern Approach, 2nd Ed., Russell

Additional Resources:

McAfee Memorial Library - Online information, links, electronic databases and the Online catalog. Contact the library for further assistance via email or at 800-270-4347.
Career Counseling - The Career Development Center (CDC) provides services for all stages of career development.  The mission of the CDC is to provide the career planning tools to ensure a lifetime of career success.
Park Helpdesk - If you have forgotten your OPEN ID or Password, or need assistance with your PirateMail account, please email helpdesk@park.edu or call 800-927-3024
Resources for Current Students - A great place to look for all kinds of information http://www.park.edu/Current/.


Course Description:
The student will learn the terminology and methods used in a variety of  artificial-intelligence (AI) areas. These topics will be covered: history of  artificial intelligence, search techniques, knowledge representation. In  addition, one or more of these topics will be covered: expert systems,  uncertainty, case-based reasoning, neural networks, vision, robotics. The  student may use various AI tools, Lisp, and/or Prolog for AI projects.

Educational Philosophy:
I will do my best to present the material in an understandable and enjoyable manner.  However, I cannot do the learning for you, so you must take personal responsibility for your education.  Part of that responsibility involves respecting those around you and their right to learn.  Outside conversation should be kept out of the classroom.  Tardiness is also a disruption and should be avoided unless absolutely necessary.

Learning Outcomes:
  Core Learning Outcomes

  1. Explain the history of artificial intelligence.
  2. Explain and trace various search algorithms.
  3. Solve first-order logic problems.
  4. Explain knowledge representation techniques.
  5. Do one or two of these:
  6. - Solve problems involving uncertainty.
  7. - Explain and trace machine learning techniques including neural network learning.
  8. - Explain and analyze vision concepts.
  9. - Explain and analyze robotics concepts.
  10. Write programs that implement artificial intelligence algorithms for some of the learning outcomes items.


Core Assessment:

All Park University courses must include a core assessment that measures the relevant Departmental Learning Outcomes.  The purpose of this assessment is to determine if expectations have been met concerning mastery of learning outcomes across all instructional modalities. The core assessment for this course is a final exam which counts for 20% of the grade. Questions on the final exam will be developed to test at least eight of the ten course core objectives.

Link to Class Rubric

Class Assessment:
There will be daily quizzes starting the second class period.  The quizzes will be worth 10% of your final grade and will cover material reviewed up to that point.  There will be between 6 and 8 quizzes, but only 4 to 5 will count towards your final grade.  I will use your top grades.  Since I treat the quizzes in this way, quizzes cannot be made-up for any reason.  There will also be weekly assignments.  These assignments will count for 60% of your final grade.  There will be a final exam on the last day of class covering all material from the beginning.  This exam will count for 20% of your final grade.   Your participation in class, which also includes attendance and classroom behavior,  will count for the remaining 10% of your final grade.

Grading:
Grading Scale:  The following grading scale will be used.  A = 90% or higher, B = 80-89.9%, C = 70-79.9%, D = 60-69.9%, F = Below 60%.  Extra credit will NOT be given to offset low scores or absences.

Late Submission of Course Materials:
Assignments should be turned in at the beginning of class.  Late assignments must be approved by me. All absences must be made up by HANDING IN the completed assignment as soon as possible after the absence. Work must be shown that indicates how each answer was obtained, wherever possible.  Failure to make up an absence results in a reduction of 1% of the final grade for each absence.  If extenuating circumstances arise, please make them known to me so that I can work with you in your situation. Four (4) unexcused absences will force an "Academic Withdrawal" to occur.  Only 1 "two-week" T.D.Y. will be allowed during the course.   When you turn in an assignment, include your full name, the date, and the assignment number in the upper right corner.  Concerning grading, I am human and I will make mistakes.  You have until the next class period to return an assignment to me if you feel I graded it incorrectly.  I will review the assignment and return points to you as needed.  However, whether I have made a mistake or not, assignments cannot be returned for review after the next class period.  I will be happy to review the issue, but no more points will be awarded. My late policy is as such:  There will be an automatic 24-hour grace period after an assignment is due during which I will not deduct points.  This grace period is useful if you have car trouble, get sick, or have any other situation that requires missing class.  After this grace period, 10 points will be deducted for every day the assignment is late, including weekends.  Assignments more than 11 days late will not be accepted.

Classroom Rules of Conduct:
I expect you to conduct yourselves in a professional manner.  You should respect both yourself and those around you.  Outside conversation has no place during class time.  There will be periodic breaks during class.  Any conversation with others not relating to the class should be kept to this time.  I will not tolerate any rude comments, including discriminatory or sexual comments, and I will dismiss students from the class, if I feel it is necessary.  I think a learning environment based on mutual respect is beneficial to everyone.

Course Topic/Dates/Assignments:
Assignments will be determined weekly based on class progress, and they will include book and programming assignments. Some assignments will be assigned as homework, and others will be completed in class. I try to make assignments that reflect what you have learned to that point, so while I do have an agenda, I will be flexible according to how the class is progressing.

Academic Honesty:
Academic integrity is the foundation of the academic community. Because each student has the primary responsibility for being academically honest, students are advised to read and understand all sections of this policy relating to standards of conduct and academic life.   Park University 2008-2009 Undergraduate Catalog Page 87
One note:I encourage you to work with others to learn and understand the material better, but any work you submit must be wholly your own.If I suspect any students of cheating, I will address the issue with those students first, but I reserve the right to send the issue up for resolution.

Plagiarism:
Plagiarism involves the use of quotations without quotation marks, the use of quotations without indication of the source, the use of another's idea without acknowledging the source, the submission of a paper, laboratory report, project, or class assignment (any portion of such) prepared by another person, or incorrect paraphrasing. Park University 2008-2009 Undergraduate Catalog Page 87

Attendance Policy:
Instructors are required to maintain attendance records and to report absences via the online attendance reporting system.

  1. The instructor may excuse absences for valid reasons, but missed work must be made up within the semester/term of enrollment.
  2. Work missed through unexcused absences must also be made up within the semester/term of enrollment, but unexcused absences may carry further penalties.
  3. In the event of two consecutive weeks of unexcused absences in a semester/term of enrollment, the student will be administratively withdrawn, resulting in a grade of "F".
  4. A "Contract for Incomplete" will not be issued to a student who has unexcused or excessive absences recorded for a course.
  5. Students receiving Military Tuition Assistance or Veterans Administration educational benefits must not exceed three unexcused absences in the semester/term of enrollment. Excessive absences will be reported to the appropriate agency and may result in a monetary penalty to the student.
  6. Report of a "F" grade (attendance or academic) resulting from excessive absence for those students who are receiving financial assistance from agencies not mentioned in item 5 above will be reported to the appropriate agency.

Park University 2008-2009 Undergraduate Catalog Page 89-90
Please contact me if you have an emergency or are expecting to be absent.  I will not always be able to answer my phone depending on what time it is and where I am.  I should be available by phone between the hours of 6 P.M. and 10:00 P.M. on Thursdays, Fridays, Saturdays, and Sundays.  However, the best way to reach me is by email.  I check my email regularly even when I am at work, so I can respond quicker in this manner.  Please feel free to send me emails, but include CS 305 Artificial Intelligence in the subject line.  Please call me only if you have not been able to reach me any other way, or it is an emergency.

Disability Guidelines:
Park University is committed to meeting the needs of all students that meet the criteria for special assistance. These guidelines are designed to supply directions to students concerning the information necessary to accomplish this goal. It is Park University's policy to comply fully with federal and state law, including Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act of 1990, regarding students with disabilities. In the case of any inconsistency between these guidelines and federal and/or state law, the provisions of the law will apply. Additional information concerning Park University's policies and procedures related to disability can be found on the Park University web page: http://www.park.edu/disability .



Rubric

CompetencyExceeds Expectation (3)Meets Expectation (2)Does Not Meet Expectation (1)No Evidence (0)
Synthesis                                                                                                                                                                                                                                                  
Outcomes
2, 7                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 
The artifact demonstrates the student ability to creatively apply prior knowledge and skills to produce an original narrative. Synthesis is demonstrated by correctly answering 2 out of 2 questions regarding: (a) future developments in Artificial Intelligence (b) comparison of neural network approach with traditional approach. The artifact demonstrates the student ability to creatively apply prior knowledge and skills to produce an original narrative. Synthesis is demonstrated by correctly answering 1 out of 2 questions regarding: (a) future developments in Artificial Intelligence (b) comparison of neural network approach with traditional approach. The artifact demonstrates the student ability to creatively apply prior knowledge and skills to produce an original narrative. Synthesis is demonstrated by correctly answering 0 out of 2 questions regarding: (a) future developments in Artificial Intelligence (b) comparison of neural network approach with traditional approach. The artifact demonstrates the student ability to creatively apply prior knowledge and skills to produce an original narrative. Synthesis is not demonstrated by answering any regarding: (a) future developments in Artificial Intelligence (b) comparison of neural network approach with traditional approach. 
Analysis                                                                                                                                                                                                                                                   
Outcomes
1, 2                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 
The artifact demonstrates the student ability to differentiate information in an AI environment. Analysis is demonstrated by correctly answering 2 out of 2 questions regarding: (a) describe state-space search (b) compare the methods to search state space. The artifact demonstrates the student ability to differentiate information in an AI environment Analysis is demonstrated by correctly answering 1 out of 2 questions regarding: (a) describe state-space search (b) compare the methods to search space The artifact demonstrates the student ability to differentiate information in an AI environment. Analysis is demonstrated by correctly answering 0 out of 2 questions regarding: (a) describe state-space search (b) compare the methods to search space The artifact demonstrates the student ability to differentiate information in an AI environment. Analysis is not demonstrated by not answering any  questions regarding: (a) describe state-space search (b) compare the methods to search space 
Evaluation                                                                                                                                                                                                                                                 
Outcomes
2, 3                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 
The artifact demonstrates the student ability to judge relative value of information based on prior knowledge. Evaluation is demonstrated by correctly answering 2 out of 2 questions regarding: (a) compare state space reduction methods (b) compare the performance of these methods using the big O notation. The artifact demonstrates the student ability to judge relative value of information based on prior knowledge. Evaluation is demonstrated by correctly answering 1 out of 2 questions regarding: (a) compare state space reduction methods (b) compare the performance of these methods using the big O notation. The artifact demonstrates the student ability to judge relative value of information based on prior knowledge. Evaluation is demonstrated by correctly answering 0 out of 2 questions regarding: (a) compare state space reduction methods (b) compare the performance of these methods using the big O notation. The artifact demonstrates the student ability to judge relative value of information based on prior knowledge. Evaluation is not demonstrated by correctly answering questions regarding: (a) compare state space reduction methods (b) compare the performance of these methods using the big O notation. 
Terminology                                                                                                                                                                                                                                                
Outcomes
1, 5                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 
The artifact demonstrates the student ability to proficiently use terminology related to specific course area. Use of terminology is demonstrated by correctly answering 2 out of 2 questions regarding (a) the Agent approach (b) identify the components of a neural network. The artifact demonstrates the student ability to proficiently use terminology related to specific course area. Use of terminology is demonstrated by correctly answering 1 of 2 questions regarding (a) the Agent approach (b) identify the components of a neural network. The artifact demonstrates the student ability to proficiently use terminology related to specific course area. Use of terminology is demonstrated by correctly answering 0 out of 2 questions regarding (a) the Agent approach (b) identify the components of a neural network. The artifact demonstrates the student ability to proficiently use terminology related to specific course area. Use of terminology is not demonstrated by answering any questions regarding (a )the Agent approach (b) identify the components of a neural network. 
Concepts                                                                                                                                                                                                                                                   
Outcomes
4, 7                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 
The artifact demonstrates student ability to recognize and articulate concepts relevant to core course topics. Recognition and articulation is demonstrated by correctly answering 2 out of 2 questions regarding: (a) the advantages of neural networks. (b)  disadvantages of neural networks. The artifact demonstrates student ability to recognize and articulate concepts relevant to core course topics. Recognition and articulation is demonstrated by correctly answering 1 out of 2 questions regarding: (a) advantages of neural networks. (b) disadvantages of neural networks. The artifact demonstrates student ability to recognize and articulate concepts relevant to core course topics. Recognition and articulation is demonstrated by correctly answering 0 out of 2 questions regarding: (a) advantages of neural networks. (b) disadvantages of neural networks. The artifact demonstrates student ability to recognize and articulate concepts relevant to core course topics. Recognition and articulation is not demonstrated by correctly answering any questions regarding: (a) advantages of neural networks. (b)  disadvantages of neural networks. 
Application                                                                                                                                                                                                                                                
Outcomes
9                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
The artifact demonstrates student ability to use principles as they relate to core course topics. Application is demonstrated by correctly answering 2 out of 2 questions regarding: (a) developing an expert system. (b) testing the expert systems in a real-world environment. The artifact demonstrates student ability to use principles as they relate to core course topics. Application is demonstrated by correctly answering 1 out of 2 questions regarding: (a) developing an expert system. (b) testing the expert systems in a real-world environment. The artifact demonstrates student ability to use principles as they relate to core course topics. Application is demonstrated by correctly answering 0 out of 2 questions regarding: (a) developing an expert system. (b) testing the expert systems in a real-world environment. The artifact demonstrates student ability to use principles as they relate to core course topics. Application is not demonstrated by answering  questions regarding: (a) developing an expert system. (b) testing the expert systems in a real-world environment. 
Whole Artifact                                                                                                                                                                                                                                             
Outcomes
6                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
The artifact demonstrates student ability to use accepted methods and standards in developing an expert system. Ability is demonstrated by correctly answering 2 out of 2 questions regarding: (a) develop a classical expert system (b) develop a fuzzy logic expert system. The artifact demonstrates student ability to use accepted methods and standards in developing an expert system. Ability is demonstrated by correctly answering 1 out of 2 questions regarding: (a) develop a classical expert system (b) develop a fuzzy logic expert system. The artifact demonstrates student ability to use accepted methods and standards in developing an expert sysyem. Ability is demonstrated by correctly answering 0 out of 2 questions regarding: (a) develop a classical expert system (b) develop a fuzzy logic expert system. The artifact demonstrates student ability to use accepted methods and standards in developing an expert system. Ability is not demonstrated by answering any questions regarding: (a) develop a classical expert system (b) develop a fuzzy logic expert system. 
Component                                                                                                                                                                                                                                                  
Outcomes
6, 7                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 
The artifact demonstrates student ability to use accepted methods and standards in performing specific software analysis and design activities. Ability is demonstrated by correctly answering 2 out of 2 questions regarding: (a) Comparison of LISP and Prolog (b) Comparison of LISP and Java. The artifact demonstrates student ability to use accepted methods and standards in performing specific software analysis and design activities. Ability is demonstrated by correctly answering 1 out of 2 questions regarding: (a) Comparison of LISP and Prolog (b) Comparison of LISP and Java. The artifact demonstrates student ability to use accepted methods and standards in performing specific software analysis and design activities. Ability is demonstrated by correctly answering 0 out of 2 questions regarding: (a) Comparison of LISP and Prolog (b) Comparison of LISP and Java. The artifact demonstrates student ability to use accepted methods and standards in performing specific software analysis and design activities. Ability is not demonstrated answering any questions regarding: (a) Comparison of LISP and Prolog (b) Comparison of LISP and Java. 

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Last Updated:12/17/2008 2:37:45 PM