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Department of Computer Science and Engineering

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CSCE 420: Introduction to Artificial Intelligence

Instructor: Dr. Dylan Shell

Office:HRBB 333B
Phone:(979) 845-2369
Email:dshell_at_cs.tamu.edu
Web:http://robots.cs.tamu.edu/dshell/cs420
Office hours:Wednesdays, 4pm-5pm, and by appointment.

TA Information

Name:Changjoo Nam
Office:HRBB 2nd floor, 214
Email:changjoo.nam_at_tamu.edu
Office hours:Wednesday 2pm-3pm (and by appointment)
Mailbox:On HRBB 3rd floor.

Fall 2012

Lecture Time:Mondays, Wednesdays and Fridays, 3pm-3:50pm.
Lecture Location:HRBB 113

Fundamental concepts and techniques of intelligent systems; representation and interpretation of knowledge on a computer; search strategies and control; active research areas and applications such as notational systems, natural language understanding, vision systems, planning algorithms, intelligent agents and expert systems.

The course is a broad survey that will require a significant amount of reading with simple introductory programming in different languages. It will provide an understanding of the state of the practice of AI and set the foundation for further study in agency, fuzzy logic, neural networks, robotics, uncertainty, and computer vision.

Prerequisites

CPSC 411 Design and Analysis of Algorithms (which has CPSC 221 Data Structures and Algorithms and CPSC 315 Programming Studio as prerequisites). CPSC 311 may be substituted for CPSC 411 if the student has taken CPSC 221 and 315.

Learning Outcomes or Course Objectives

  • List the basic techniques for creating intelligent programs. This will be measured by quizzes, and tests.
  • Create a successful program illustrating the operation of one of these methods. This will be measured by the final project.
  • Apply the right programming language or technique to the right problem. This will be measured by exercises.
  • Be able to evaluate a proposed AI application for likelihood of success. This will be measured by the inclusion of case studies on homework and tests.
  • Be able to discern sensationalism from science on the possible impact of AI on society. This will be measured by the final.

Textbook

Artificial Intelligence: A Modern Approach 3rd Edition by Stuart Russell and Peter Norvig, 2009.

Grading Policies

Grades will be based on:
30%: Three tests
20%: Daily class quizzes
20%: Programming exercises
15%: Final project
15%: Take-home final
The grading scale is:
A 90-100
B 80-89
C 70-79
D 60-69
F 59 or below

Course Topics, Calendar of Activities, Major Assignment Dates

Syllabus topics and readings are subject to change, exact dates depend on class progress

WeekTopicReading
27 AugIntroduction, Intelligent Agents1, 2.
3 SepSearch3.
10 SepSearch for games, etc4 & 5.
17 SepConstraint satisfaction6.
24 SepKnowledge representation7.
1 OctLogic8.
8 OctInference9.
15 Oct Fuzzy logic(Notes)
29 Oct Planning10.
1 NovLearning18.1-18.4
8 Nov Learning18.5, 18.6
12 NovNeural networks, reinforcement learning18.7, 21.1, 21.2.
19 NovNatural language processing22.
26 NovPhilosophical foundations26.
 Dec 5: Reading days
 Dec 8: Take home final due.

Homework
These homeworks are to used for your own revision and self-assessment.
Homework 1  Solution
Homework 2  Solution
Review for the first class test: Review (With Answers)
Review for the second class test: Review (With Answers)

Quizes
We will have approximately one quiz per week, sometimes one every two weeks. The quiz will only cover material that has been previous covered in class.
This is an example quiz: Spring 2010, Quiz 1
Here is another example quiz: Spring 2010, Quiz 2
Here is a third quiz: Spring 2010, Quiz 3

Due DateClass Tests and Assignments
23 SepProgramming Assignment on Search.   Now posted here
1 OctTest 1
28 OctProgramming Assignment on Logical Inference.  Now posted here
2 NovTest 2
3 DecProgramming Assignment on Learning.   Now posted here | Data Files
8 DecTake home final due.  Now posted here
11 Dec Final Project Presentations in Final Slot (10:30am-12:30pm).  Now posted here

Students with Disabilities

The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact Disability Services, in Cain Hall, Room B118, or call 979-845-1637. For additional information visit http://disability.tamu.edu.

Academic Integrity

For additional information please visit: http://www.tamu.edu/aggiehonor
"An Aggie does not lie, cheat, or steal, or tolerate those who do."

Policy on Missed Work

Material missed due to recognized absences (illness with doctor's excuse, death in the family) can be made up for full credit. Late material is accepted solely at the discretion of the instructor, at least 1 class period's prior notice must be given for consideration of acceptance of late material.

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