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CS 305 Intro to Artificial Intelligence
Burns, James D.


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 Intro to Artificial Intelligence

Semester

F2T 2010 DL

Faculty

Burns, James D.

Title

Senior Instructor

Degrees/Certificates

MS, Systems Engineering, Naval PostGraduate School
BS, Business Administration, University of South Carolina

Daytime Phone

410 294 7725

E-Mail

james.burns@park.edu

scgolfer@vzw.blackberry.net

Class Days

TBA

Class Time

TBA

Prerequisites

CS 352

Credit Hours

3


Textbook:

 Russell and Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall (Second Edition), 2003.

Textbooks can be purchased through the MBS bookstore

Textbooks can be purchased through the Parkville Bookstore

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/.
Advising - Park University would like to assist you in achieving your educational goals. Please contact your Campus Center for advising or enrollment adjustment information.
Online Classroom Technical Support - For technical assistance with the Online classroom, email helpdesk@parkonline.org or call the helpdesk at 866-301-PARK (7275). To see the technical requirements for Online courses, please visit the http://parkonline.org website, and click on the "Technical Requirements" link, and click on "BROWSER Test" to see if your system is ready.
FAQ's for Online Students - You might find the answer to your questions here.


Course Description:
CS305 Introduction to Artificial Intelligence: 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. Prerequisite: CS352. 3:0:3

Educational Philosophy:
I believe that while learning is an intensely individual, it can be facilitated by sharing ideas with others.  I learn more each term than anyone else, because I can learn from the whole class.

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:
    1. Solve problems involving uncertainty
    2. Explain and trace machine learning techniques including neural network learning
    3. Explain and analyze vision concepts
    4. Explain and analyze robotics concepts.
  6. 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:

Each student will be asked to complete a variety of assignments to assess how well he/she has mastered the Core Learning Outcomes for the course.   An overview of the assignments is provided below:

 

Learning Outcome

Method of Assessment

Description

1-6

- Homework

- Participation in group or individual discussion assignments

- Exam

Short answer questions that require students to apply all objectives

2-6

- Homework

- Participation in group or individual discussion assignments

- Exam

Solve problem(s) by applying an appropriate artificial intelligence algorithm

2-5

- Homework

- Participation in group or individual discussion assignments

- Exam

Trace an artificial intelligence algorithm

6

Homework

Implement an artificial intelligence algorithm with a working program

1-6

Class Project

Conducts research into an area of artificial intelligence or create a complex artificial intelligence program

6

- Homework
- Exam

Given a problem description, write a solution using pseudocode or a programming language

 

Grading:

Points Awarded

Assignment

% of Course Grade

Total Points

Homework #1

6

60

Homework #2

6

60

Homework #3

6

60

Homework #4

6

60

Homework #5

6

60

Homework #6

6

60

Project

30

300

Final Exam

20

200

Class Discussion (Individual and Group Assignments)

14

140

Grading Scale

A = 90- 100% of points awarded
B = 80-89% of points awarded
C = 70-79% of points awarded
D = 60-69% of points awarded

F = < 60% of points awarded

Grading Standards

Assignments will be graded according to the criteria outlined below:

Homework

  • Programs:
    • Complete assignment by due date
    • Program accomplishes all task required in the assignment
    • Original methods of accomplishing tasks are used when a specific approach is not required
  • Written Assignments:
    • Complete assignment by due date
    • Insights are germane to the question
    • Choices and use of supporting evidence
    • Grammar and mechanics

Project

  • Program
    • Complete by due date
    • Includes required deliverables
    • Problem selected and approach demonstrate originality
    • Degree of difficulty
  • Paper
    • Complete by due date
    • Logic of organization and use of prescribed formats
    • Includes opening paragraph the clearly describes the topic
    • Displays in-depth understand of topic--does not restate source material
    • Degree of difficulty
    • Integration of source material
    • Grammar and mechanics

Discussion Assignments

  • Complete Discussion assignments by due date
  • Respond to discussion questions witl applicable information and concepts shared in readings
  • Individual Assignments:
    • Present original thoughts and ideas
    • Respond to other's postings, as applicable, and avoid simple agreement/disagreement with, or restating of other's postings
  • Group Assignments:
    • Present original thoughts and ideas
    • Contribute sufficiently to overall group activity

Late Submission of Course Materials:
Late work will be accepted during Weeks 1 through 7 but up to 5% of the total grade may be deducted for each late any assignment is turned in late.  No late work will be accepted after Week 8, which is the last week of the course.

Classroom Rules of Conduct:
Courteous discourse and working together is the key to mastering this difficult subject.

Course Topic/Dates/Assignments:

Topic

Date

Assignments

Date Due

Introduction to Artificial Intelligence

Week 1

Reading Assignment

Homework #1

Discussion Assignment

All assignments due Sunday at midnight

Problem Solving and Searching

Week 2

Reading Assignment

Homework #2

Discussion Assignment

All assignments due Sunday at midnight

Knowledge and Reasoning

Week 3

Reading Assignment

Homework #3

Discussion Assignment

All assignments due Sunday at midnight

Uncertain Knowledge and Reasoning

Week 4

Reading Assignment

Homework #4

Discussion Assignment

All assignments due Sunday at midnight

The Learning Agent

Week 5

Reading Assignment

Homework #5

Discussion Assignment

All assignments due Sunday at midnight

Perceiving and Acting

Week 6

Reading Assignment

Homework #6

Discussion Assignment

All assignments due Sunday at midnight

Conclusions

Week 7

Reading Assignment

Discussion Assignment
Class Project Due
All assignments including the Project are due Sunday at midnight

 

Final Exam

Week 8

Final Exam

Discussion Assignment

All other assignments due Sunday at midnight

 

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 students and faculty members are encouraged to take advantage of the University resources available for learning about academic honesty (www.park.edu/current or http://www.park.edu/faculty/).from Park University 2010-2011 Undergraduate Catalog Page 92

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. from Park University 2010-2011 Undergraduate Catalog Page 92-93

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.
ONLINE NOTE: An attendance report of "P" (present) will be recorded for students who have logged in to the Online classroom at least once during each week of the term. Recording of attendance is not equivalent to participation. Participation grades will be assigned by each instructor according to the criteria in the Grading Policy section of the syllabus.

Park University 2010-2011 Undergraduate Catalog Page 95-96

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:10/3/2010 6:32:40 PM