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Wentworth
Institute of Technology
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Computer
Science Department
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Summer
2006
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Comp490 Intro.
to Artificial Intelligence
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Instructor:
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Department Office:
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Karina
Assiter, Ph.D.
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DOBBS 006
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DOBBS
303
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617-989-4272
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617-989-4835
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assiterk@wit.edu
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Course Management
System:
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All course material (syllabus,
assignments, project information, exam
reviews, faculty schedule, calendar
items, discussion topics, etc,..)
will be available on WebCT to students
enrolled in the course. If you do not
see WebCT on LConnect, or if this course
is not listed in WebCT, please notify
the instructor. Students should login to
WebCT regularly to check for
announcements, emails, date changes,
discussion topics, etc,... |
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Please select the
area of your interest:
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Course Description
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Covers
introduction to LISP programming language, symbolic computation, knowledge
representation, search strategies and expert systems.
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Course Goals
and Learning Objectives
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After
this course, students will understand the broad range of artificial
intelligence (AI) topics such as machine vision, machine learning and
machine evolution. Students will also be proficient in implementing
selected methods in natural language parsing, machine learning and action
planning.
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Pre-requisite/Co-requisite
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COMP310 Object-Oriented
Data Structures
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Students must have successfully completed the prerequisite(s) in order to
take this course and receive an acceptable grade. Grades of "IC",
"W", and "F" do not satisfy prerequisites nor does taking the prerequisites concurrent with the
course. Prerequisites or written permission of the instructor will be
withdrawn from the course.
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Required Text
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Nils J. Nilsson, "Artificial Intelligence: A New
Synthesis", Morgan Kaufmann Publishers, 1998.
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Suggested
Readings
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- Colin Allen & Maneesh Dhaget,
"Lisp Primer" link (from Texas A&M
via Web).
- Various handouts (will be
made available on WebCT)
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Attendance Policy
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- Regular attendance at every
class is expected; anyone who fails to meet this requirement may be
requested to withdraw from Wentworth.
- Students with poor
attendance may be withdrawn from class with a grade of "WA".
- Attendance policies are
fully explained in the Wentworth Catalogue.
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Assignments/Submitted
Work/Late Work
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- Approximately 10-12
assignments (one per week).
- Late assignments get a 10%
deduction per week.
- If all assignments submitted
on time, lowest grade will be dropped.
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Grading and Student
Evaluation System
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The
final grade will be determined according to:
- Homework - 30% (includes periodic presentations)
- Exams (3) - 30%
(given on WebCT)
- Final Project - 20% (includes
a presentation)
- Discretionary - 20% (attendance, in-class
and WebCT participation)
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Topics
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Week
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Topics
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Readings
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Notes
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1
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Introduction
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Nillson Chapter 1
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2
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Stimulus-Response
Agents
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Nillson Chapter 2
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3
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Neural
Networks
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Nillson Chapter 3
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4
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Machine
Evolution (GA's)
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Nillson Chapter 4
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Exam 1
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5
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Robot
Vision (Huffman, Waltz, et al)
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Nillson Chapter 6
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6
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Agents
that Plan (State Spaces)
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Nillson Chapter 7
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7
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Uninformed
Search (BFS,DFS, ID)
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Nillson Chapter 8
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8
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Heuristic
Search (A*)
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Nillson Chapter 9
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Exam 2
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9
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Propositional
Calc. & Resolution
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Nillson Chapter 13 &14
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10
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The Predicate Calculus
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Nillson Chapter 15
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11
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- Communication among
agents
- Lisp introduction
- Intro to parsing
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· Nillson Chapter 24
· Allen & Dhaget 27, 59-60, 106
· Allegro
Common Lisp handout
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Exam 3
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12
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Final
Projects
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Please note:
- The above topic list is
subject to change in the event of extenuating circumstances.
- The version of the syllabus that appears on
WebCT is the final word.
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