Thu Apr 9 13:22:02 2009
| Approvals Received: |
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| Approvals Pending: | College/Dean > LE > Catalog > PeopleSoft Manual Entry | |
| Effective Status: | Active | |
| Effective Term: | 1103 - Spring 2010 | |
| Course: | CSCI 4511W | |
| Institution: | UMNTC - Twin Cities | |
| Career: | UGRD | |
| College: | TIOT - Institute of Technology | |
| Department: | 11108 - Computer Science & Eng | |
| General | ||
| Course Title Short: | Intro: Artificial Intelligence | |
| Course Title Long: | Introduction to Artificial Intelligence | |
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Max-Min Credits for Course: |
4.0 to 4.0 credit(s) | |
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Catalog Description: |
Introduction
to AI. Problem solving, search, inference techniques. Knowledge
representation. Planning. Introduction to machine learning.
Robotics. The Lisp programming language. |
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| Print in Catalog?: | Yes | |
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CCE Catalog Description: |
<no text provided> | |
| Grading Basis: | Stdnt Opt | |
| Topics Course: | No | |
| Honors Course: | No | |
| Delivery Mode(s): | Classroom | |
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Instructor Contact Hours: |
4.0 hours per week | |
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Years most frequently offered: |
Every academic year | |
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Term(s) most frequently offered: |
Spring | |
| Component 1: |
LEC (with final exam) |
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Auto-Enroll Course: |
No | |
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Graded Component: |
LEC | |
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Academic Progress Units: |
Not allowed to bypass limits. 4.0 credit(s) |
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Financial Aid Progress Units: |
Not allowed to bypass limits. 4.0 credit(s) |
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Repetition of Course: |
Repetition not allowed. | |
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Course Prerequisites for Catalog: |
CSci 2011 or #;cannot be taken for grad CSci cr. | |
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Course Equivalency: |
CSci 4511W/5511 | |
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Consent Requirement: |
No required consent | |
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Enforced Prerequisites: (course-based or non-course-based) |
No prerequisites | |
| Editor Comments: | <no text provided> | |
| Proposal Changes: | <no text provided> | |
| History Information: | <no text provided> | |
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Faculty Sponsor Name: |
Maria Gini | |
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Faculty Sponsor E-mail Address: |
gini@cs.umn.edu | |
| Liberal Education | ||
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Requirement this course fulfills: |
None | |
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Other requirement this course fulfills: |
None | |
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Criteria for Core Courses: |
Describe how the course meets the specific bullet points for the proposed core
requirement. Give concrete and detailed examples for the course syllabus, detailed
outline, laboratory material, student projects, or other instructional materials or method.
Core courses must meet the following requirements:
<no text provided> |
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Criteria for Theme Courses: |
Describe how the course meets the specific bullet points for the proposed theme
requirement. Give concrete and detailed examples for the course syllabus, detailed outline,
laboratory material, student projects, or other instructional materials or methods. Theme courses have the common goal of cultivating in students a number of habits of mind:
<no text provided> |
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| Writing Intensive | ||
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Propose this course as Writing Intensive curriculum: |
Yes | |
| Question 1: |
What
types of writing (e.g., reading essay, formal lab reports, journaling)
are likely to be assigned? Include the page total for each writing
assignment. Indicate which assignment(s) students will be required to
revise and resubmit after feedback by the instructor or the graduate TA. Students will be asked to do other various types of writing, including: 1. a report on the class project. The project, which is required from everyone, will be proposed by each student on a topic of his/her own choice related to any aspect of the material covered in the course, such as an application of search algorithms, strategies and heuristics for computer games, development and use of ontologies, theorem proving, applications of planning. The report will be due in different parts: a 1-2 pages proposal will be due at week 8 in the semester, a 4-5 pages intermediate report with a description of the problem to be studied and related literature review will be due at week 12, and a 10-12 pages of polished final report will be due at the end of the semester. Students will be allowed to resubmit their intermediate report, and will receive suggestions on how to improve their writing. The intermediate report will be incorporated into the final report. The report will be assessed for structure, content, and clarity of writing. 2. a short summary and critique of a paper published in the field. This will be done at least twice during the semester, after students are given instructions on how to read and review a technical paper in the field of Artificial Intelligence. Each critique will be limited to 1 page. Critiques will be reviewed by another student and discussed in class in small groups. Students will be allowed to resubmit the critiques after receiving feedback from other students. The critiques will then be graded by the instructor or the TA for content, structure, and clarity of writing. 3. some short essay questions will be included in the homeworks. The amount of writing and length of the essays will likely change every semester. Most of the essays will be short, limited to less than one page each. Typically the students will be asked to write 2 to 3 such short essays during the semester. These essays will be graded by the TA or the instructor. 4. writing computer programs with appropriate comments and related documentation is an essential form of writing for computer scientists. Students will be given 2-3 programming assignments during the semester and asked to provide written explanations and documentation for their programs. 5. students will also be required to contribute to the class discussion in the on-line class forum. |
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| Question 2: |
How does assigning a significant amount of writing serve the purpose
of this course? Good skills in writing and expressing ideas are essential for Artificial Intelligence. Artificial Intelligence requires, even more than other parts of Computer Science, the ability to think logically and clearly, the ability to understand issues, articulate ideas, motivate opinions, and describe choices. Writing will help the students articulate their ideas, explain their opinions, and support their choices. |
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| Question 3: |
What types of instruction will students receive on the writing aspect
of the assignments? Guidelines and material on technical writing will be posted on the class webpage and will be covered briefly in class. The material will span from short guidelines on technical writing, to pointers to comprehensive writing material and grammar rules, to material on formatting technical papers using Latex, to specific guidelines and grading rubrics for the writing assignments, and examples of the types of writings expected in the course. The students' writings will be reviewed for technical content, structure, clarity, and quality of writing. Most of the writings will be reviewed and graded by the instructor or the TA(s), with help from the students themselves for the critique papers. The critique papers will be initially reviewed by other students in the class, using informal discussion groups, and will then be graded by the instructor. Students will be allowed to resubmit them after they have been reviewed by other students. The project report will be submitted in multiple rounds, with feedback on writing given to the students on their intermediate report. Students will be allowed to resubmit the intermediate report and will use it in their final report. |
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| Question 4: |
How will the students' grades depend on their writing performance?
What percentage of the overall grade will be dependent on the quality and level of the students'
writing compared with the course content? The students' grades will depend on their writing performance. No student will be allowed to pass the class without satisfactory performance in writing. At least 15% of the class grade will depend on the project report. The critique papers and short essay questions in the homeworks will count for 10% of the grade. Various in class writing activities and writing on the class forum will count for 10% of the grade. |
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| Question 5: |
If graduate students or peer tutors will be assisting in this course,
what role will they play in regard to teaching writing? The TA(s) will be closely supervised by the instructor. They will receive instruction from the professor in how to evaluate the content, structure, and clarity of the specific types of writings required for the course. |
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| Question 6: |
How will the assistants be trained and
supervised? The TA(s) will be supervised by the instructor. The Department will provide training as needed. All the Ph.D. students in the Department take in their first year a two semesters sequence on "Introduction to Research in Computer Science," which, among other things, requires them to write a literature review and a short research proposal, and provides instructions on how to read and critique articles in the various subfields of Computer Science. This will provide training for the TAs on the types of writings used in Computer Science and will prepare them well to assess the types of writings required by the undergraduate students. |
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| Question 7: |
Write up a sample assignment handout here for a paper
that students will revise and resubmit after receiving feedback on the initial
draft. This assignment is to familiarize you with some of the ideas (and hopefully to dispel the myths) about Artificial Intelligence. Do the following: 1. Read an article of your choice from The Singularity Issue of IEEE Spectrum, June 2008. This is a recent issue of the Spectrum magazine that includes a collection of articles written by a variety of scientists and philosophers. The articles are short and written for a general technically educated public. 2. Write one page summarizing succinctly the major points of the article you read and with your own comments on the article. Here are a few questions to help you thinking about the contents and the structure of your writing. What does the article cover? Why did you select it? Does the article present compelling arguments and/or scientific evidence to support its claims? Is the article well organized and well structured? Does it deliver what it promises in the abstract and introduction? Are the figures in the article (if any) useful to clarify the contents? Are there enough bibliographical references to help the reader explore the topics more in depth? 3. Bring your writing to class. We will discuss the articles you have read in small groups in class. You will be asked to read and criticize the writing of another student in your group. You will then be allowed to rewrite your critique before submitting it for grading. |
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Readme link.
Course Syllabus requirement section begins below
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| Course Syllabus | ||
| Course Syllabus: |
For new courses and courses in which changes in content and/or description and/or credits
are proposed, please provide a syllabus that includes the following information: course goals
and description; format;structure of the course (proposed number of instructor contact
hours per week, student workload effort per week, etc.); topics to be covered; scope and
nature of assigned readings (text, authors, frequency, amount per week); required course
assignments; nature of any student projects; and how students will be
evaluated. The University "Syllabi Policy" can be
found here
The University policy on credits is found under Section 4A of "Standards for Semester Conversion" found here. Course syllabus information will be retained in this system until new syllabus information is entered with the next major course modification. This course syllabus information may not correspond to the course as offered in a particular semester. (Please limit text to about 12 pages. Text copied and pasted from other sources will not retain formatting and special characters might not copy properly.) CSci 4511W: Sample Syllabus Class Information Time/Room: TBA Instructor: Dr. Maria Gini (gini at cs.umn.edu) office hours: Monday TBA or by appointment in EE/CS 5-213, (612) 625-5582. Address:4-192 EE/CSci Bldg, 200 Union St. SE, Mpls,MN 55455 TAs: TBA Textbook Stuart Russell and Peter Norvig "Artificial Intelligence. A modern approach. 2nd Edition", Prentice-Hall, 2003. (Chapters 1-11, 18, 20, 25). You should go to http://aima.cs.berkeley.edu/lisp/doc/install.html to download the Lisp software from the texbook. We will use it for some homeworks. You'll need reference material on Lisp. Here are some choices: • Lamkins, Successful Lisp: How to Understand and Use Common Lisp, bookfix.com, 2004. • Graham, ANSI Common Lisp, Prentice Hall, 1996 The Lisp Code, the text of the first two chapters, and many articles on Lisp are available from http://www.paulgraham.com/ All class material will be posted at http://www.itlabs.umn.edu/classes/Spring-2010/csci4511w/. Prerequisites Students are expected to have the following background: • Knowledge of basic computer science principles. • Knowledge of data structures (graphs and trees). • Knowledge of formal logic (propositional and predicate logic). Course Description: This course provides a technical introduction of fundamental concepts of artificial intelligence (AI) and their applications to real world problems. Topics include: history of AI, agents, search (search space, uninformed and informed search, constraint satisfaction, game playing), knowledge representation (logical encodings of domain knowledge, logical reasoning systems), planning, an introduction to machine learning, and the language Lisp. The course is suitable for students who want to explore the field of Artificial Intelligence and build the foundations for more advanced work in AI. Course Work and Learning Objectives You are expected to read approximately 30 pages/week from the textbook. You are expected to spend 12 hours/week on average for the course, including class time, lab time, reading the textbook, studying, and doing the homework. The course is writing intensive and will include writing instruction and various forms of writing: • A report on your class project will be due in 3 parts: a proposal (1-2 pages), an intermediate report (4-5 pages), and a final report (10-12 pages). You will be allowed to resubmit your intermediate report after receiving feedback. You will incorporate your intermediate report into your final report. • We will read at least two articles in addition to the material in the textbook. You will write a summary and critique (1 page) for each article and you will have your writing read and criticized by another student in the class during a small group discussion in class. You will be allowed to rewrite it and resubmit it. • Some homeworks will include a short essay question (less than one page each). • Contributions to the discussion on the class forum are expected from everyone in the class. Course Requirements • four written homeworks (36% of the grade). Homeworks will include problem solving, short essays, and Lisp programming problems; • two short written critiques of published articles (4%); • one project (20% of the grade). The project is on a topic of your own choice and requires that you write a 10-12 pages of final polished report; • participation to class discussion and other in class activities (10% of the grade); • two in class midterm exams (each 10% of the grade), • one final exam (10% of the grade). Academic Integrity All work submitted for this class must represent your own individual effort unless group work is explicitly allowed. You are free to discuss course material and approaches to problems with classmates, the TAs, and the professor (and you are encouraged to do so), but you should never misrepresent someone else's work as your own. It is also your responsibility to protect your work from unauthorized access. Collaboration on homework or exams is cheating and grounds for failing the course. Any student caught cheating will receive an F as a class grade and the University policies for cheating will be followed. In addition, any graduate student caught cheating will be subject to the Department policy on cheating. Policy on Exams and Grading Grades will be assigned on the following scale: 93% and up will earn you an A, 90% to 93% an A-, 87% to 90% a B+, 83% to 87% a B, 80% to 83% a B-, 75% to 80% a C+, 65% to 75% a C, 60% to 65% a C-, 55% to 60% a D+, 50% to 55% a D, below 50% an F. Exams are open books and notes. Late homeworks will lose 10% of the maximum total points for every weekday late. Late homeworks will be accepted up to a week after they are due. Keys will be distributed in class a week after the homework is due. Tentative Class Schedule (subject to changes) Ch Topics Assignments due AIMA Slides Week 1 1, 2 Intro to AI. Intelligent Agents Chapter 2 Week 2 3 Problem Solving and Search Homework 1 Chapter 3 Week 3 3,4 Search Algorithms Chapter 4.1-2 Week 4 4 Heuristic Search Homework 2 Chapter 4 Week 5 5 Constraint Satisfaction Chapter 5 Week 6 6 Game Playing First Midterm Exam Chapter 6 Week 7 6 Game Playing, Game Theory Week 8 7 Propositional Logic Project Proposal Chapter 7 Week 9 8, 9 First-Order Logic Chapter 8 and 9 Week 10 18 Machine Learning, Decision trees Homework 3 Chapter 18 Week 11 20 Reinforcement Learning Chapter 20 Week 12 10 Knowledge Representation Second Midterm Exam Project Intermediate Report Week 13 25 Introduction to Robotics Chapter 25 Week 14 11 Planning Homework 4 Chapter 11 Week 15 Wrap up Project Report Final Exam |
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