CSE352
ARTIFICIAL INTELLIGENCE
SUMMER 2008


Course Information


News:

  • Please email and discuss with the Professor the subject of your presentation as soon as possible.
  • PRESENTATION PROPOSAL is due Tuesday June 10.
  • Presentations STARTS Thursday, June 12.
  • SCHEDULES for Presentations and Homeworks are below and in the Syllabus.
  • PROJECT DESCRIPTION is in the Syllabus.
  • Homework 1 is in Downloads.
  • Lecture Notes: Introduction to Learning, Preprocessing, and Supervised Lerning: Classification are Downloads

    • Time:

    Tuesday, Thursday, 6:00 - 9:25 pm

    Place:

    Physics 117

    Professor:

    Anita Wasilewska

    1428 CS Building; 632-8458
    e-mail: anita@cs.sunysb.edu
    Office Hours: Tue, Th 5:00 - 5:45 pm, and by appointment

    Teaching Assistant:

    Fatima Zarinni
    e-mail: fzarinni@cs.sunysb.edu
    Office Hours: by appointment

    Book:

    The Essence of Artificial Intelligence
    Allison Cawsey
    Prentice Hall, 1998

    General Course Description:

    Artifficial Intelligence is a broad and well established field. The AI textbooks seem to be getting longer and longer. Our cource textbook attemts to reverse this trend. It provides a concise and accessible introductionto the field.
    The course will closely follow the book and is designed to give a broad, yet in-depth overview of different fields of AI. It will examine the most recognized techniques in a more rigorous detail. For this part we will provide detailed lecture notes distributed in class and available on the web. It also will explore the newest trends and developments of the field in form of students talks based on newest research and applications from the field.

    Student Information

  • Students ATTENDENCE is essential for the course.

    Project Data

  • Play around with the data and familiarize yourself with it (DOWNLOAD: bakarydata.xls )

    • Students Input

  • Here are the links for the Loebner Prize.
    Please send me more, if you find some interesting pages, or articles.

    • Loebner Prize Main Page
    Minsky Comments
    2005 Contest
    2005 Winner (Jabberwacky)

    Presenations schedule

  • PRESENTATION PROPOSAL is due Tuesday June 10.
  • Presentation 1 Title: t.b.a, Thursday, June 12
  • Presentation 2 Title: t.b.a, Thursday, June 19
  • Presentation 3 Title: t.b.a, Thursday, June 26
  • Presentation 4 Title: t.b.a, Thursday, July 3
  • PROJECT PRESENTATIONS, Thursday, July 10

    • Homeworks and Tests Schedule

  • Homework 1 due Tuesday, June 17
  • Homework 2 due Tuesday, June 24
  • Homework 3 due Tuesday, July 1
  • FINAL due THURSDAY, July 10, or any day before.

    • DOWNLOADS

    SUMMER 2008 SYLLABUS
    Homework 1

    Lecture Notes:

    01. Introduction to Learning
    02. Data Preprocessing
    03. Classification (1) - Supervised Learning
    04. Classification (2) - Testing
    05. Classification by Decision Tree
    06. Classification By Neural Networks
    07.Bayesian Classification
    08. Genetic Algorithms

    DATASETS

    Datasets for learning, data mining and knowledge discovery
    University California Irvine KDD Archive
    World Bank datasets
  • Please email and discuss with the Professor the subject of your presentation as soon as possible.
  • I would like the presentations to be given in-between my lectures.