1. CSE 571 (11147) Artificial Intelligence (MW 3:15 – 4: 30 PM, ECA A219) Instructor: Chitta Baral Office hours: Tuesday 2 to 5 PM

2. Meaning of the word: ``intelligence'' 1 (a) The capacity to acquire and apply knowledge. (b) The faculty of thought and reason. (c) Superior powers of mind. See Synonyms at mind. 2 An intelligent, incorporeal being, especially an angel. 3 Information; news. See Synonyms at news. 4 (a) Secret information, especially about an actual or potential enemy. (b) An agency, staff, or office employed in gathering such information. (c) Espionage agents, organizations, and activities considered as a group Source: The American Heritage® Dictionary of the English Language, Fourth Edition Copyright © 2000 by Houghton Mifflin Company. Published by Houghton Mifflin Company. All rights reserved.

3. Meaning of the word: ``intelligence'' n 1: the ability to comprehend; to understand and profit from experience [ant: stupidity] 2: a unit responsible for gathering and interpreting intelligence 3: secret information about an enemy (or potential enemy); "we sent out planes to gather intelligence on their radar coverage" 4: new information about specific and timely events; "they awaited news of the outcome" [syn: news, tidings, word] 5: the operation of gathering information about an enemy [syn: intelligence activity, intelligence operation] Source: WordNet ® 1.6, © 1997 Princeton University

4. Artificial Intelligence Based on the above, `artificial intelligence' is about the science and engineering necessary to create artifacts that can – acquire knowledge, i.e., can learn and extract knowledge; and – reason with knowledge (leading to doing tasks such as planning, explaining, diagnosing, acting rationally, etc.),

5. Two main parts of this course Knowledge representation, reasoning (and declarative problem solving) –60% from the text book -- Aug 25th to Oct 22 –10% from the book `Causality' by Judea Pearl and papers by Judea Pearl and Joe Halpern; and on Bayes' nets -- Oct 29th, Nov 3, 5 Learning –15% on learning logical rules such as Progol, FOIL etc -- Nov 10,12,17; –15% on learning Bayes' nets, causal structures etc. -- Nov 19-26, Dec 1

6. Syllabus from the text book Chapter 1 (Sections 1.1-1.3). Chapter 2 Chapter 3 (Sections 3.1, 3.1.1-3.1.3, 3.1.5, 3.2, 3.2.1, 3.2.4, 3.4, 3.4.1) Chapter 4 Chapter 5 (Sections 5.1-5.4, 5.6) Chapter 8 (Sections 8.1-8.3) Time line: –Aug 25, 27, Sept 3, 8 -- Ch1, Ch 8 (Smodels and DLV syntax) –Sept 10, 15, 17, 22 -- Ch 2 and 3 –Sept 24, 29, Oct 1 -- Ch 4 –Oct 6, 8, 13, 15, 20, 22 -- Ch 5, some of Ch 8 Several papers for the other parts (to be listed)

7. Grading Two tests (No finals) 30% –Test dates (Test 1 -- Oct 27; Test 2 -- Dec 3) One project 30% (Due by Dec 5th, demo during Dec 1-5) –Sept 29th -- I will suggest a list of ideas –Start discussing mine and other ideas by Oct 1 st –Finalize project proposal by Oct 15th; –First Status report Nov 5 th –Second Status report Nov 17th Homework & programming assignments 20% Class notes (making slides -- due in 7 days) 10% Class participation 10% –percentage of classes you have asked non-trivial question and answered questions; attendance will be taken in every class; –coming late after the attendance has been taken will result in being marked absent and will count negatively. first class disruption -- arriving late or a similar activity - without prior permission will count -1% of the grade; the next one -2%; and so on.)

8. Modus Operandi Students will be assigned material to read. They have to come prepared to the class where I will ask questions and clarify things. This will happen during the first 60 minutes of the class. In the last 15 minutes of the class I will motivate the content to be discussed in the next class. Each class one student will take notes and make slides.