Spring2009.CSCI470CourseSyllabus History

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* We will engage engage in [[http://en.wikipedia.org/wiki/Inquiry-based_science | inquiry-based learning]], and in-class activities.
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* To develop working knowledge, in terms of understanding the theory and being able to
design/implement working applications, of one AI area.
to:
* To develop working knowledge, in terms of understanding the theory and being able to design/implement working applications, of one AI area.
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* To gain fundamental knowledge on AI, including its definition(s), history, and main
philosophical issues.
to:
* To gain fundamental knowledge on AI, including its definition(s), history, and main philosophical issues.
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* To understand the fundamental differences between symbolic, statistical, and
connectionist approaches.
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* To understand the fundamental differences between symbolic, statistical, and connectionist approaches.
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Exam 25%, and Class Participation 5%.
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Exam 20%, and Class Participation 10%.
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||![-College of Charleston-] ||! [-January 9, 2009-]||
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||![-College of Charleston-] ||! [-January 12, 2009-]||
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'''Tentative Outline:'''
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'''Textbook:'''
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Syllabus, Survey, Intro to Media Computing, Algorithms, MIT's ''Scratch'', Intro to Music Composition (guest lecture), Audio, MP3, MIDI, Sounds, ''Audacity'', Intro to Art (guest lecture), Intro to ''Python'', Images, and ''other topics'' as time permits.\\
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Stuart Russell and Peter Norvig (2003), "[[http://aima.cs.berkeley.edu/ | Artificial Intelligence: A Modern Approach]]", 2nd ed. Prentice Hall Series in Artificial Intelligence.
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'''Textbook:'''
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'''References:'''
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Stuart Russell and Peter Norvig (2003), "[[http://aima.cs.berkeley.edu/ | Artificial Intelligence: A Modern Approach]]", 2nd ed. Prentice Hall Series in Artificial Intelligence.
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Additional reading materials will provided via handouts, the [[http://www.cs.cofc.edu/~manaris/?n=Spring2009.CSCI470 | class website]].\\
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'''References:'''
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'''Learning Outcomes:'''
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Additional reading materials will provided via handouts, the [[http://www.cs.cofc.edu/~manaris/?n=Spring2009.CSCI470 | class website]].\\

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'''Learning Outcomes:'''
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* You are expected to attend all classes (your class participation grade depends on it).
* You are expected to take good notes during
lecture (bring a notebook and pen).
to:
* You are expected to attend all classes.
* You are expected to take good notes during
lecture.
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** You may have up to 4 excused absences.
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* Since we are in a lab, you must use the computers only as directed (e.g., no checking email, or playing games) during class.
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* Assignment grades will be based on creative inspiration, design, style, and correctness of result.
* Submission instructions will be provided for each assignment.\\
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* Assignment grades will be based on design and style as well as correctness of result.
* Submission instructions will be provided for each assignment.
* Do not submit programs with syntax errors. They are not eligible for credit
.\\
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||![-College of Charleston-] ||! [-January 9, 2009-]||

!!%center%CSCI 470 – Artificial Intelligence
!!!%center%Course Syllabus

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'''Professor:'''
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Dr. Bill Manaris\\

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'''Office:'''
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Room: 223 J.C. Long Building \\
Phone: (95)3-8159 \\
E-mail: manarisb@cofc.edu \\
Web: http://www.cs.cofc.edu/~manaris/\\

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'''Office Hours:'''
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Monday, Wednesday from 10:30AM - noon.\\
Tuesday, Thursday from 10:45AM - noon.\\
Other hours available by appointment.\\

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'''Course Description:'''
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A course introducing fundamental techniques for artificial intelligence. Among topics covered are heuristic search, knowledge representation, intelligent agents, reasoning, neural networks, genetic algorithms, and artificial intelligence programming. Additional topics may include Bayesian networks, natural language processing, machine learning, rule-based systems, robotics, and discovery informatics. Artificial intelligence programming techniques will also be introduced.

''Prerequisites:'' Computer Science 320 and Mathematics 307.

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'''Tentative Outline:'''
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Syllabus, Survey, Intro to Media Computing, Algorithms, MIT's ''Scratch'', Intro to Music Composition (guest lecture), Audio, MP3, MIDI, Sounds, ''Audacity'', Intro to Art (guest lecture), Intro to ''Python'', Images, and ''other topics'' as time permits.\\

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'''Textbook:'''
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Stuart Russell and Peter Norvig (2003), "[[http://aima.cs.berkeley.edu/ | Artificial Intelligence: A Modern Approach]]", 2nd ed. Prentice Hall Series in Artificial Intelligence.

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'''References:'''
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Additional reading materials will provided via handouts, the [[http://www.cs.cofc.edu/~manaris/?n=Spring2009.CSCI470 | class website]].\\

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'''Learning Outcomes:'''
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* To gain fundamental knowledge on AI, including its definition(s), history, and main
philosophical issues.
* To understand knowledge representation schemes and related issues.
* To understand the fundamental differences between symbolic, statistical, and
connectionist approaches.
* To gain experience in programming with a programming language used in AI applications.
* To develop working knowledge, in terms of understanding the theory and being able to
design/implement working applications, of one AI area.
* To develop an understanding of AI’s impact on today's society.

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'''Grading:'''
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To receive a passing grade for the course, you must average a passing grade on each of the
following: assignments, tests, and final exam.

'''Scale:''' A: 90-100; B: 80-89; C: 70-79; D: 60-69; F: < 60. [-(The grades of B+/–, C+/–, and D+/– may be given at the professor's discretion.)-]

'''Final Grade Computation:''' Assignments (4-6) 30%, Tests (2) 40%, Comprehensive Final
Exam 25%, and Class Participation 5%.

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'''Honor Code:'''
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* '''You must do your assignments alone''' (or with your teammates, for group assignments).
* You are not allowed to discuss assignments and possible solutions with any person other than the instructor (or with your teammates, for group assignments). Any violation of these rules is an honor offense.
* On assignments you will be asked to identify the person(s) you received help from, if any.
* Also see the College of Charleston '''[[http://www.cofc.edu/about/documents/handbook.pdf | Student Handbook]]''', especially sections on ''The Honor Code'' (p. 10), and ''Student Code of Conduct'' (p. 12). There is other useful information there.\\

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'''Test Policies:'''
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* Attendance at tests is mandatory. You must complete tests with no discussion or sharing of information with other students.
* Calculators, computers, cell phones, etc. may not be used during a test, unless otherwise directed.\\

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'''Classroom Policies:'''
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* You are expected to attend all classes (your class participation grade depends on it).
* You are expected to take good notes during lecture (bring a notebook and pen).
* You are expected to participate in class with questions and invited discussion.
* If you miss class:
** You are responsible for announcements made in class, assignment due dates, etc.
** You must [[http://www.cs.cofc.edu/~manaris/?n=Main.AbsenceMemoInformation | get an absence memo from the Associate Dean of Students Office]].
** You may have up to 4 excused absences.

* We will engage engage in [[http://en.wikipedia.org/wiki/Inquiry-based_science | inquiry-based learning]], and in-class activities.

* Since we are in a lab, you must use the computers only as directed (e.g., no checking email, or playing games) during class.
* You should '''turn off all electronic devices''' (e.g., cell phones, pagers, etc.).

* In summary, you should contribute positively to the classroom learning experience, and respect your classmates right to learn (see College of Charleston '''[[http://www.cofc.edu/about/documents/handbook.pdf | Student Handbook]]''', section on ''Classroom Code of Conduct'' (p. 62)).\\

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'''Assignment Policies:'''
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* Assignment grades will be based on creative inspiration, design, style, and correctness of result.
* Submission instructions will be provided for each assignment.\\

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'''Late Policy:'''
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* You have '''four "late" days''' for the whole semester. You may use these days as you wish for assignment submission. If you use them up, no late assignments will be accepted.
* '''If you submit everything on time''' (i.e., use no late days), you will earn an additional '''2.5 bonus points''' on your course grade.
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