COURSE SYLLABUS CAP 4601 Introduction to Artificial Intelligence Summer Semester 2013

This first course in Artificial Intelligence (AI) is designed to expose the student to both the breadth and depth of the subject. Topics include problem solving, knowledge and reasoning, acting logically, uncertain knowledge and reasoning, learning, and communicating, perceiving and acting. This introduction will develop each of these topics using the intelligent agent model popularized by Russell & Norvig. This course will cover some of the useful mathematics, data structures, and algorithms used in various fields of AI. C++ (specifically, C++11) and relevant libraries will be used to implement these concepts.

Corequisite: Data Structures, Algorithms and Generic Programming (COP 4530)

Even though COP 4530 is just a corequisite for CAP 4601, this course will leverage information throughout COP 4530 and will use mathematics and computer science from the entire co- and prerequisite tree of COP 4530: Computer Organization I (CDA 3100), Discrete Mathematics I (MAD 2104), Object Oriented Programming (COP 3330), Programming I (COP 3014), Introduction to UNIX (COP 3353), Precalculus Algebra (MAC 1140), and College Algebra (MAC 1105) or their equivalents. These co- and prerequisites will be enforced. Students not meeting the co- or prerequisite requirements will be dropped from the class.

Since selections from calculus, trigonometry, and linear algebra will be quickly reviewed prior to the topics in AI where they are used, Calculus with Analytic Geometry I (MAC 2311) and Precalculus Algebra/Trigonometry (MAC 1147) or their equivalents are also strongly recommended.

The course will use the following libraries:

1. C++ Standard Library
2. Open Source Computer Vision (OpenCV)
3. Boost Graph Library (BGL)

The course will address topics in the following order:

1. Mathematics Review & C++11 Quick Start
2. Intelligent Agents
3. Learning
   1. Supervised Learning
      1. Regression
      2. Classification
   2. Unsupervised Learning
4. Problem Solving
   1. Search
      1. Uninformed
      2. Informed
      3. Optimization
5. Knowledge and Reasoning
   1. Knowledge Representation in Certain Domains
   2. Propositional Logic
   3. First-Order Logic
   4. Inference
6. Uncertain Knowledge and Reasoning
   1. Knowledge Representation in Uncertain Domains
   2. Probability
   3. Probabilistic Inference
   4. Probabilistic Reasoning over Time
7. Classical Planning
8. Communicating, Perceiving, and Acting
   1. Natural Language Processing
   2. Computer Vision
   3. Robotics

Course Grading:

• Each week, students will complete homework assignments consisting of both written work and programming tasks.
• Each student will take two proctored exams:
  • A Midterm Exam during the 7th week and
  • A cumulative Final Exam during the 12th week.
• Each student will be graded on Participation. Participation will consist of posting substantive, non-trivial, and original comments to the Discussion Board on the course's Blackboard site by either creating new threads or replying to existing threads. Participation will be graded weekly and will require posting at least one substantive, non-trivial, and original comment. "Substantive," "non-trivial," and "original" will be determined by the instructor. Students are encouraged to post multiple comments each week.
• The week before the end of the semester, each student will submit an eight-page conference-style research paper with a working proof of concept in C++ supporting that research.
• During the last week of the semester, each student will critically review three of the research papers submitted by their peers.

See the Course Calendar for details on exam scheduling and due dates for deliverables.

Delivery Modes: This class will have students attending in one mode:

• Distance Learning Online (Sections 01 - 07)

Participation: Each week, there will be a new Discussion Forum on the BlackBoard course site at https://campus.fsu.edu for the current course topics. Participation will be graded based on comments posted in these Discussion Forums. Each student is expected to post at least one substantive, non-trivial, and original comment relating to that week's material. If students ask questions relating to the week's material, then this graded comment can be the reply to one of those questions; insofar as, that reply is substantive and non-trivial. The instructor will inform each student when they have posted a substantive and non-trivial comment. Students are encouraged to post multiple comments each week.

Online Students: The online sections will use an asynchronous, class-paced format delivered via the Internet for student activities and assessments.

Asynchronous: Discussion Forums allow students to interact on their own time each week rather than at a time chosen for the entire class to interact simultaneously.

Class-paced: Assignments have weekly deadlines (due dates) so that the entire class progresses at the same pace weekly but not necessarily daily. Assignment due dates and exam windows are the same for all students.

Web Format: The web delivery format is based on the Blackboard system which will be used to receive assignments, obtain lecture materials, submit assignments, contact the instructor, conduct class discussions and contact other students. The instructor may also be contacted via telephone or e-mail (or even snail mail) or, during the regularly scheduled class meeting time and scheduled office hours.

Instructor Contact: It is critical that online students be given the same level of contact to faculty that is available to on-campus students. This contact is provided through extensive use of discussion boards. The instructor will monitor these discussion boards on a daily basis. In addition to the Forums described above, there will be a weekly office hours using an interactive video chat facility.

Instructor(s):

• Joshua Burkholder
• Chris Lacher

Course Objectives: At the end of this course, the student should be able to accomplish the following:

• Define intelligence from multiple perspectives
• Define and give examples of artificial intelligence from multiple perspectives
• Define rationality and a rational agent in the context of artificial intelligence
• Define, diagram, and give examples of the following intelligent agents:
  • Simple reflex agent
  • Model-based reflex agent
  • Goal-based agent
  • Utility-based agent
  • Learning agent
• Define and specify task environment characteristics for any given problem in artificial intelligence:
  • Fully Observable versus Partially Observable
  • Single Agent versus Multiagent
  • Deterministic versus Stochastic
  • Episodic versus Sequential
  • Static versus Dynamic
  • Discrete versus Continuous
  • Known versus Unknown
• Define learning in the context of artificial intelligence
• Define supervised and unsupervised learning and identify when supervised and unsupervised learning should be used
• Define and give examples of regression and classification in supervised learning and identify when regression or classification should be used
• Describe and use various supervised and unsupervised learning algorithms and specify the model characteristics in those algorithms:
  • Global versus Local
  • Hierarchical versus Non-Hierarchical
  • Parametric versus Non-Parametric
• Describe how search is used to solve problems in artificial intelligence
• Describe and use uninformed and informed search algorithms and optimizations
• Describe various knowledge representations in certain and uncertain domains
• Use Propositional and First-Order Logic for Certain Reasoning
• Describe the Unification, Forward Chaining, and Backward Chaining algorithms in Inference
• Describe and use Bayes' Rule, Conditional Independence, and Probability for Uncertain Reasoning
• Describe and use Probabilistic Inference
• Describe and use Probabilistic Reasoning over Time
• Describe Classical Planning
• Define and give examples of Natural Language Processing
• Define and give examples of Computer Vision
• Define and give examples of Robotics
• Write a research paper on artificial intelligence for an academic conference

Course Materials: The student should have the following text:

• Russell, Stuart and Norvig, Peter (2010). Artificial Intelligence: A Modern Approach, 3rd Edition. Prentice Hall, Upper Saddle River, New Jersey. ISBN 978-0-13-604259-4.

COURSE POLICIES

First Day Attendance Policy: Official university policy is that any student not attending the first class meeting will be automatically dropped from the class. For distance students, this policy is interpreted as answering "True" to the First Day Attendance Quiz in the Blackboard site.

Regular Attendance Policy: The University requires attendance in all classes. Attendance in distance classes shall mean regular access to the course web site via https://campus.fsu.edu and regular participation in the class discussion forums. Here, "regular" shall mean a substantial amount of time on a weekly basis. Note that individual access statistics are maintained by Blackboard.

Excused absences include documented illness, deaths in the immediate family and other documented crises, call to active military duty or jury duty, religious holy days, and official University activities. Accommodations for these excused absences will be made and will do so in a way that does not penalize students who have a valid excuse. Consideration will also be given to students whose dependent children experience serious illness.

Late Deliverables Policy: Deliverables (Assignments, Participation, Projects, and Peer Review) are due by 11:59 PM Eastern Daylight Time (UTC - 4 Hours) on the due date posted on the Course Calendar. Late deliverables will immediately incur a 50% penalty and may be turned in up to seven days past their original due date. Example: If a 100 point assignment is turned in one second past 11:59 PM EDT on the date due, then the maximum number of points that student can receive is 50 points. If the student scores 80% on that assignment, the student will receive 40 points.

After a deliverable is more than seven days past due, that deliverable will be recorded as a grade of zero (0).

There is one exception: the deliverables due the final week cannot be turned in late. All deliverables received after 11:59 PM EDT on 02 AUG 2013 will be recorded as a grade of zero (0).

Exceptions to this Late Deliverables Policy will be the same as the Exam Makeup Policy.

Proctored Exam Policy: All exams must be proctored and taken at an approved testing site during the exam window. It is the student's responsibility to arrange for proctored exams in compliance with the FSU standards. Go to http://distance.fsu.edu/students/testing/ for complete information on setting up a proctored exam site.

Exam Makeup Policy: An exam missed without an acceptable excuse will be recorded as a grade of zero (0). The following are the only acceptable excuses:

• If submitted prior to the day of the scheduled exam:
  • A written and signed explanation as to why the exam will missed. Illness or required professional travel are acceptable, while discretionary or personal travel are not. In any case the explanation should be accompanied by corroborating documentation, including names and contact information, and the explanation must be accepted by the instructor prior to missing the exam.
  • Evidence from an University official that you will miss the exam due to University sanctioned travel or extracurricular activity.
• If submitted on or after the day of the scheduled exam:
  • A note from a physician, university dean, spouse, parent, or yourself indicating an illness or other extraordinary circumstance that prevented you from taking the exam and could not be planned for in advance. Again, corroborating information should be supplied.

Missed exams with acceptable excuse will be made up or assigned the average grade of all other exams, at the option of the course instructor.

Missed, and acceptably excused, final exams will result in the course grade of 'I' and must be made up in the first two weeks of the following semester.

Grade of 'I' Policy: The grade of 'I' will be assigned only under the following exceptional circumstances:

• The final exam is missed with an accepted excuse for the absence. In this case, the final exam must be made up during the first two weeks of the following semester.
• Due to an extended illness or other extraordinary circumstance, with appropriate documentation, the student is unable to participate in class for an extended period. In this case, arrangements must be made to make up the missed portion of the course prior to the end of the next semester.

Completion of Work Policy: To be eligible for the grade of A or A-, passing versions of all assignments must be submitted.

Syllabus Change Policy: Except for changes that substantially affect implementation of the evaluation (grading) statement, this syllabus is a guide for the course and is subject to change with advance notice. Such notice will be in the form of an Announcement and a Discussion Board posting on the BlackBoard course site at https://campus.fsu.edu.

ACADEMIC HONOR POLICY

The Florida State University Academic Honor Policy outlines the University's expectations for the integrity of students' academic work, the procedures for resolving alleged violations of those expectations, and the rights and responsibilities of students and faculty members throughout the process. Students are responsible for reading the Academic Honor Policy and for living up to their pledge to ". . . be honest and truthful and . . . [to] strive for personal and institutional integrity at Florida State University." (Florida State University Academic Honor Policy, found at http://fda.fsu.edu/Academics/Academic-Honor-Policy/.)

All students are expected to uphold the Academic Honor Policy. Please note the following items are defined and made violations by the policy:

1. Plagiarism
2. Cheating
3. Unauthorized Group Work
4. Fabrication, Falsification, and Misrepresentation
5. Multiple Submission
6. Abuse of Academic Materials
7. Complicity in Academic Dishonesty
8. Attempted ...

Checking for Plagiarism: FSU subscribes several databases of papers and computer source code that have been previously published or turned in for credit in university courses worldwide. Student work may be checked in one or more of these databases for originality. Note that turning in work that contains quoted material with adequate citation from any source is considered plagiarism and a violation of the FSU honor code.

AMERICANS WITH DISABILITIES ACT

Students with disabilities needing academic accommodation should:

1. Register with and provide documentation to the Student Disability Resource Center; and
2. Bring a letter to the instructor indicating the need for accommodation and what type. This should be done during the first week of class.

This syllabus and other class materials are available in alternative format upon request.

For more information about services available to FSU students with disabilities, contact the:

Student Disability Resource Center
874 Traditions Way
108 Student Services Building
Florida State University
Tallahassee, FL 32306-4167
(850) 644-9566 (voice)
(850) 644-8504 (TDD)
sdrc@admin.fsu.edu
http://www.disabilitycenter.fsu.edu

(This syllabus and other class materials are available in alternative format upon request.)

EMERGENCY MANAGEMENT INFORMATION

Information regarding the status of FSU in an emergency situation may be obtained from the following sources:

• For information specific to the Panama City Campus go to the FSUPC web page at http://www.pc.fsu.edu or call the Campus Hotline number 850-770-2000
• For information related to FSU in general and the Tallahassee Campus go to the FSU alerts web page at http://www.fsu.edu/~alerts/
• For state-wide and national information, go to the Florida Division of Emergency Management information pages at http://www.floridadisaster.org