[ General Information
| Course Outline
| Lectures
| Handouts
| Other Pointers
| Requirements
]
[ Announcements
]
Course description: This course is for students interested in learning some unifying as well as diversifying cutting-edge technologies and applications of computer science, centered around the idea of intelligent agents. The main topics include problem solving and search, knowledge representation and inference, planning, uncertainty reasoning, and learning; we will also discuss natural language processing, computer vision, and robotics. | Prerequisites: CSE 214 and 303; or permission of the instructor. | Credits: 3.
Instructor: Annie Liu | Email: liuATcsDOTsunysbDOTedu | Office: Computer Science 1433 | Phone: 632-8463.
Hours: TueThu 8:20-9:40AM, in Computer Science 2129. | Office hours: TueThu 9:40-11, in CS 1433.
Textbook: Artificial Intelligence: A Modern Approach, 2/E, by Stuart Russell (UC Berkeley) and Peter Norvig (Google), Prentice Hall, 2003. ISBN: 0-13-790395-2.
Grading: 20% for weekly or bi-weekly programming or written assignments, 20% for a project, and 30% each for two exams. Programming assignments and project are to be done in pairs, the rest individually. Written assignments given as practice for exams will not be graded, but solutions will be provided and each one not turned in will receive -5%. No credit for late submissions.
Course homepage: http://www.cs.sunysb.edu/~liu/cse352/, containing all course-related information.
We will start with an overview of the scope, problems, approaches, and applications of artificial intelligence and present the view of AI as the enterprise of designing intelligent agents.
We will then study two most basic topics of AI: (i) problem solving and search, which includes problem description, exhaustive and heuristic search, constraint satisfaction, and game playing, and (ii) knowledge representation and inference, which includes propositional logic, first-order logic, and inference methods and systems. We will also discuss additional techniques for the topic of planning. This will be followed by the first exam.
We will then introduce two important distinguished areas of AI: (i) uncertainty reasoning, which includes uncertainty and probability, Bayesian networks and reasoning, temporal probabilistic reasoning and speech recognition, and decision making, and (ii) learning, which includes inductive learning, decision tree learning, and neural networks. This will be followed by the second exam.
Finally, we will discuss topics on agents communicating, perceiving, and acting, which include natural language processing (grammars, syntax analysis, etc), vision (image formation, object recognition, etc), and robotics (robots, configuration spaces, motion planning).
Assignments will be given mostly before the spring break, and each
one will be due in class on the due date, usually when the next course
work is given. The project will be given after the spring break and
due immediately after the last class. See detailed schedules below,
but there might be small changes based on the pace of the lectures.
Handout Q: Questionnaire Slides for Ch.1: Artificial Intelligence
Slides for Ch.3: Solving Problems by Searching
Slides for Ch.7: Logical Agents
(pdf)
Slides for Ch.11: Planning
(pdf)
Slides for Ch.13: Uncertainty
(pdf)
Slides for Ch.18: Learning and Observations
(pdf)
Slides for Ch.22: Communication
(pdf)
Handout A1: Assignment 1: Intelligent Agent
Handout A2: Assignment 2: Programming Recursion and Symbolic Manipulation
Handout A3: Assignment 3: Programming A* Search
Handout A4: Assignment 4: Exercise Problems for Exam 1
Handout A5: Assignment 5: Programming with Logical Relations and Rules
Handout A6: Assignment 6: Exercise Problems for Exam 2
Handout E1: Exam 1
Handout E2: Exam 2
Handout P: Project: An Artificial Intelligence System
Ghostscript, Ghostview and
GSview: Ghostview and GSview are for viewing and printing
Postscript documents (some of the handouts for this course will be in
this format). If you use Linux, then this software is already
installed on your machine. On Windows, you need to download both
Ghostview and Ghostscript (and also some fonts). Unzip Ghostview and
run setup.exe. It will unpack and install the rest.
The gzip homepage: GNU zip for compression.
Some programming assignments will be in Java, others in a language
that you choose and can justify. Knowledge of Lisp would be useful.
We will also learn some Prolog. Basic ideas of data structures and
complexity are needed. Calculus comes in handy in one or two places.
You should learn all information on the course homepage. Check the
homepage periodically for Announcements.
Do all course work. The homeworks and projects are integral parts
of the course as they provide concrete experiences with the abstract
ideas covered in the class.
Disability: If you have a physical, psychological, medical
or learning disability that may have an impact on your ability to
carry out assigned course work, please contact the staff in the
Disabled Student Services office (DSS), Room 133 Humanities,
632-6748/TDD. DSS will review your concerns and determine with you
what accommodations are necessary and appropriate. All information
and documentation of disability are confidential.
Lectures
Lecture 1 (01/23/03): Overview: course, AI problems,
approaches, history, state of art. Reading:
Ch.1. Assign 1.
Handouts
Slides for Ch.2: Intelligent Agents
Slides for Ch.4: Informed Search and Exploration
(pdf)
Slides for Ch.5: Constraint Satisfaction Problems
(pdf)
Slides for Ch.6: Adversarial Search
(pdf)
Slides for Ch.8: First-Order Logic
(pdf)
Slides for Ch.9: Inference in First-Order Logic
(pdf)
Slides for Ch.12: Planning and Acting in the Real World
(pdf)
Slides for Ch.14: Probabilistic Reasoning /Part 1
(pdf) | /Part 2
(pdf)
Slides for Ch.15: Probabilistic Reasoning over Time /Part 1
(pdf) | /Part 2
(pdf)
Slides for Ch.16: Making Simple Decisions
(pdf)
Slides for Ch.20: Statistical Learning Methods /Part on Neural Networks
(pdf)
Slides for Ch.24: Perception
(pdf)
Slides for Ch.25: Robotics
(pdf)
Handout E1S: Exam 1 Solution
Handout E2S: Exam 2 Solution
Other Pointers
Requirements
Annie Liu