Old announcements

• [11/30] In class yesterday, we covered perceptrons and just started learning about neural networks and backpropagation. Some of the topics we covered on perceptrons were: the basic algorithm, and details on choosing alpha (the learning rate) and a termination condition. We also discussed why the perceptron learning rule works --- how it is doing stochastic gradient descent. We also discussed the delta learning rule which uses an unthresholded perceptron. Oh, also "batch" approaches which do the "real" gradient descent on an error function over the entire training data set.

  Chapters 2 and 3 in our text touch on these things, but not too clearly. If you are looking for other reference material, you could try Chapter 19 of the Russell and Norvig text or the chapter in Mitchell's Machine Learning text. Both are on reserve at the library.

• [11/30] Monday's quiz will be mostly on Bayesian classifiers, though there may be a bit of perceptrons on there. Bayesian classifiers are also covered in Mitchell's Machine learning text in case you are looking for a reference.

• [11/26] Assignment 7 is out and due on Monday December 3. The Assignment 7 web page is up (with support code and 1 data set).

• [11/25] (As announced in class last week,) Tommorow's quiz will be on probability and Bayes' rule which we have covered in the past 1.5 classes. It will not cover Bayes classifiers which we will finish on Monday. A brief review of these topics can be found in sections 19.1 and 19.2 in our text. Any introductory text on probability and statistics will also cover these topics; you could also look at chapter 14 of Russell and Norvig's "Artificial Intelligence: a modern approach" which is on reserve in the library.

• [11/20] A student pointed out that the example.txt file to illustrate decision tree learning had some mistakes on page 2. (For example "patrons" was selected as the top level attribute, but it still appears as a candidate in remaining split information calculations.) I cannot reproduce the error, so I don't know what happened. I have put corrected files below in the handouts section. (This was handed out on 11/8.)

• [11/8] Monday's quiz will be entirely on decision trees. I would expect you to know basic concepts relevant to decision trees. I'd expect you to know the formula for calculating information but not for the "gain ratio" or "split information". I'd highly recommend doing the first problem from Assignment 6 for practice.

• [11/8] As announced in class today, I am throwing out Quiz 9 from this past Monday. I've deemed it not worth grading...

• [11/8] Today in class we finished up decision trees. After reviewing the concepts of classification problems and measuring information (for the "information gain" heuristic) and the basic algorithm (called ID3), we discussed:
  • a complete example (see the handout from today)
  • overfitting
  • connection between learning decision trees and search and propositional logic
  • dealing with continuous attributes
  • dealing with missing attributes
  • the "gain ratio," an alternative heuristic to "information gain"
  • rule post pruning

  This material is not covered in our text. Two references (which are both on reserve in the library) are:

  • For the basic stuff: Chapter 18 of Russell and Norvig's book "Artificial Intelligence: a modern approach"
  • For practical extensions and more advanced stuff: Chapter 3 of Mitchell's "Machine Learning" book.

• [11/7] The support code for assignment 6 is out. See the assignment 6 information page.

• [11/1] Monday's quiz will generally be on First Order Logic (FOL) and topics covered in class this week. This may include basic concepts/syntax/etc of FOL, inference in FOL (particularly using the resolution inference rule), transforming sentences into conjunctive normal form, and (quite likely) a proof using resolution.

• [10/25] Monday's quiz will cover propositional logic. There will be a proof on the quiz. You should understand the basic concepts and terminology, (e.g. completeness, soundness, inference, entailment, and so on) both intuitively and the formal definitions. Note that slides on logic were handed out in class today, are available outside my office door, and are also available in the handouts section below.

• [10/25] As I've said in class this week, I will be out of town at a conference next week. On Monday, Zie Kone will be giving a lecture and administering the quiz. On Thursday, Prof. Selmer Bringsjord from the Cognitive Sciences Department will be giving a lecture on theorem proving. I have asked him to provide some questions for the next Monday's quiz!

• [10/25] As announced in class today, the tentative schedule for the rest of the assignments is:
  • Assignment 5: Out 10/25, due 11/5 (written)
  • Assignment 6: Out 11/5, due 11/19? (programming decision tree learning)
  • Assignment 7: Out 11/19? due 12/3? (programming)

• [10/15] I've added a new section below for links.

• [10/14] As announced in class on Thursday, Monday's quiz may cover alpha-beta pruning with MINIMAX search although there will not be a problem like Problem 3 from Assignment 4. It could also cover EXPECTIMAX and the basics of iterative improvement algorithms and constraint satisfaction problems. I suggested that students read chapter 11 and look at Exercise 11.2 in the text.

• [10/12] The web tester and oracles for Problems 1 and 2 from Assignment 4 are up! (So is the "web tester tester" and a "syntax checker".) See the Assignment 4 page for details.

• [10/9] Today in class we finished game playing search. There was one handout, the slides from today's class. Remember that Problem 3 of Assignment 4 is due on Thursday. On Thursday, we will start Chapters 10 and 11 from the text (the last searching topics). The oracles for problems 1 and 2 on Assignment 3 were finished last week and are waiting to go up on the web. The testers for problems 1 and 2 should be up this week.

• [10/5] Monday's (well, Tuesday's) quiz next week will have at least one A* problem. (This is why solutions to problem 1 on assignment 3 were handed out in class on Thursday; copies are available outside my office door if you didn't get one.) You will not be expected to prove the optimality of A* but you may be expected to know its properties (with respect to optimality, completeness, etc.) It may also cover handling repeated states and minimax search (but not with alpha-beta pruning). Make sure you are up on Chapters 7-9 and 12.

• [10/5] There are two mistakes on the Assignment 3 solutions for Problem 1. In iteration 6, node G on the OPEN list has its path updated but not its cost. The cost should be 9.4, not 10.3. In iteration 5, the f value for node C on the open list should be 9.4, not 9.4.0.

• [10/4] The Assignment 4 web page is up (with support code)!

• [9/30] Tomorrow's quiz will cover the blind search (DFS, BFS, iterative deepening, and uniform cost) and heuristic search (greedy, A*). You will not be asked to prove the optimality of A*.

• [9/28] Revised slides from yesterday's class and other material are available in the handouts section and in the (new) online course material section.

• [9/24] Assignment 3 deadlines have been extended as follows:
  • Problem 1 (written A*) is still due on Thursday 9/27. The usual late policy and automatic extension apply (as amended).
  • Problems 2-4 and 6 (programming) are due at midnight Sunday night 9/30. There is no automatic extension of this deadline. The first tier late deadline is midnight Monday night 10/1, and the second tier late deadline is 10am Thursday 10/4.
  • Problem 5 (a written description of your ep-heuristic procedure) is due in class on Monday 10/1. There is no automatic extension of this deadline. The first tier late deadline is 5pm Monday 10/1. The second tier late deadline is 10am Thursday 10/4.

• [9/24] Today we went through an A* example, did an overview of the optimality proof for A*, and discussed monotonicity and the properties of A* with a monotonic heuristic. There were two handouts: Assignment 1 solutions and Assignment 2 solutions. Finish reading Chapter 9.

• [9/24] Zie Kone has added an additional office hour from 4-5 on Wednesdays.

• [9/21] Yesterday in class, we went over the implementation of the Missionaries and Cannibal problems (and breadth first search) in Scheme. We also started heuristic search and went over Greedy search and the A* algorithm (which we'll continue on Monday). There was one handout: copies of the slides I used during class. Continue reading Chapter 9 for Monday.

  Monday's quiz could cover Chapter 7, Chapter 8 through section 8.4, and Chapter 9 sections 9.1 and the first parts of 9.2 (not more than what we covered in class on Thursday). You should know the difference between state space and a search tree, the difference between states and nodes, what an admissible heuristic is, and why we like the A* search.

• [9/20] The Assignment 3 information page is up.

• [9/18] Assignment 3 is out and is due Thursday September 27. Make sure you have a CS account and kerberos password, since we expect to only be using the web tester for this next assignment. The Assignment 3 information page will be up soon...

• [9/18] Yesterday we started search, covering state space versus search trees, breadth first search, depth first search, completeness, optimality, and space and time complexity. There were two handouts: Assignment 3 and an implementation of the Missionaries and Cannibals problem in Scheme. Start reading Chapter 9 for Thursday.

• [9/14] It appears that the final examination for this course has been scheduled for Friday December 14 from 11:30am - 2:30pm. I'll confirm this later.

• [9/14] Today we covered Chapters 5 and 6 from the text. There was one handout, Scheme IV. We went over some topics from Scheme III (map, apply, and lambda) and the topics from Scheme IV (printing, begin, tail recursion, and helper functions). Monday's quiz will have some Scheme on it (list recursion, map, apply, and lambda) and topics from Chapters 4--6. In particular, there will certainly be something on Genetic Programming and probably a problem from the line labeling covered in Chapter 6.

  Read Chapters 7 and 8 for Monday when we will begin "search."

• [9/13] Please note new submission instructions for Assignment 2 if you do not have a CS account. See the Assignment 2 Submission page.

• [9/12] A student pointed out a mistake in an example on the Scheme III handout. In Section 11.1, the cond form in the change-colors procedure should be a case form instead.

• [9/11] We had to change Zie Kone's office hours. His new office hours are Wednesdays from 12-2 (or by appointment).

• [9/10] Today we talked about genetic programming from Chapter 4 of the text, covered recursion patterns, and went through some example problems. Read Chapter 6 on computer vision for Thursday.

• [9/6] Today we covered perceptrons and neural networks from Chapters 2 and 3 of the text. We did not get into the mathematical details of backpropagation. We talked about list procedures, conditionals, and the section on Scheme III on functional programming. There were two handouts: Scheme III and Assignment 2.

• [9/6] Assignment 2 is out, due Thursday September 13. Electronic turn-in details and other information will appear on the Assignment 2 information page.

• [9/6] For late Assignment 1 papers (and papers turned in under the automatic extension until midnight tonight if you signed up in class), I'd prefer receiving hardcopy. You can drop it off at my office (slip it under the door if I'm not there). However, Amos Eaton building will supposedly be locked between 6 and 7pm although I don't believe it. For this assignment, you can email your solution to our TA, Zie Kone (konez@cs.rpi.edu). Future submission by email will be at his discretion.

• [9/6] Quiz 1 is on Monday September 10. This will hopefully be a 15 minute quiz. Possible topics include Chapters 1-5 from the text and Scheme. I made a few specific comments about possible quiz questions at the end of class today. Quizzes are closed book and closed notes.

• [9/4] I updated the links to the xscheme.el and xscheme.elc files. You must have these files in place to use MIT Scheme through gnu-emacs. (Of course, this only works on UNIX systems.) See the "Getting started..." page off "The Scheme page" (below).

• [9/3] One of the links I wrote down in class for getting Scheme was incorrect. Go to "the Scheme page" (below), then to the "getting started..." page. The correct links are there.

• [8/31] Chapters 1-3 of the text are online in the class reserves section of the library. On the class reserves page, search under instructor "Huang" (evidently I'm the only one) or under course name "Introduction to Artificial Intelligence".

• [8/30] For the next class, skim through Chapter 3 of the text. We'll be covering the main ideas of this chapter in class.

• [8/30] Assignment 1 is out and due next Thursday. The Assignment 1 Page has information about this assignment (errata, clarifications, etc.) I will be updating this page regularly, so check back.

• [8/30] The bookstore is out of our textbook. They ordered more on the 28th which they expect to come in on Tuesday or Wednesday.

  In the meantime, I dropped off my copy at the library, and they will be scanning Chapters 1-3 which will be available through their class reserves system. This should probably be available before Friday afternoon.

• [8/30] Today we covered "Reactive Agents" (mostly following Chapter 2 of the text) and went over the Scheme II handout. We'll continue with the Scheme II handout next week. There were three handouts: Scheme II, Top 10 keybindings in Emacs/Edwin for MIT Scheme, and Assignment 1.

• [8/27] Today we covered "What is AI?", went over the course syllabus in detail, and started learning Scheme. There were two handouts: the course syllabus (available in the handouts section below) and the Scheme I handout.

  For Thursday's class, read Chapters 1 and 2 from our text, read the Scheme I handout, and figure out how you're going to run Scheme (download an implementation to your computer or such --- see the Scheme page listed below).