CS 151: Artificial Intelligence
Final Project
Due dates: 12/10/13 and 12/20/13 in-class

• You can develop a technique or an application, or both. For example, you might propose to implement approximate inference for Bayes nets, or you might build a naive Bayes spam filter.
• You may use any resources you can find, including code you have written for this class or other classes, code provided with the book, data you find on the web, etc. Just be sure to cite any resources.
• You should be able to find at least two papers in the literature that relate to your project. These papers should be on work that solves the same or a similar problem.
• You should aim for a project that will take about 20 hours of work per team member. This is not a lot of work, and things always take longer than you expect, so try to be conservative in what you say you will do (you can always extend it if you have extra time).

On December 10th, we will have in-class project updates. Each group will speak for (TBD) minutes and will submit a rough draft of their final write up. The goal of these presentations is to help you clarify your problem and your approach and to ensure you don't wait until the last minute to do all of the work.

For the in-class project updates, you can choose to just speak, use the white board, or prepare a short (e.g. one-slide) presentation summarizing your project. Regardless, your project updates should include:

• A clear statement of the problem
• A clear outline of the steps that you have, are, or will take to solve the problem. For example, "We've already scraped the data we'll be using from website X and website Y. Now that we have the data, we're working on extracting certain features: describe features here. Then, we're going to be using classifiers provided on website Z to do the classification. We'll evaluate our system by computing precision and recall on a set of held out data points".
• A timeline of the remaining steps to be done for your project

In addition, each group will hand in a rough draft of the final paper. Your final papers will be typed in LaTeX using the AAAI LaTeX template (see below). I highly recommend you write your rough draft in LaTeX using this template. Your rough draft should include:

• The title of the paper along with the names of the authors (i.e. team members)
• A 1-paragraph description of the problem you will solve. (To be turned into an Introduction section)
• A 1-3 paragraph description of how you plan to solve the problem. (To be turned into a System Description section)
• What results you aim to obtain and how you will evaluate your approach. (To be turned into a Results section)
• Citation information for any relevant literature. (To be turned into the Bibliography)

We'll be using our finals time slot to do project presentations. Our time slot is December 20th at 9am which is the final due date for the projects. The location is TBA.

• Why should I (or anyone else care) about what you did? (i.e. motivation)
• What specific technical problem did you solve?
• How did you solve this problem?
• Why did you choose this solution?
• How well does it work (and how do you know)?

Your presentations will be graded on:

• Content (How well did you address each of the points above)
• Organization
• Speaking style
• Your attendance at all presentations

Use the AAAI LaTeX template for formatting your papers. You can get the template files from the AAAI authors site and use them for your paper format. Your paper should be no more than 3 pages. Keep in mind that writing a paper this short takes work and planning.

The following are common sections found in research papers:

• An Introduction that motivates and describes the problem and the results at a high level.
• A Related Works section that briefly describes existing work that solves the same (or similar) problem.
• A Background section that explains any background information necessary to understand the problem or your approach.
• A System Description section that provides the details of how you constructed your system, how it works, and how you tailored the algorithms described in the previous section to the problem at hand.
• A Results section that describes how well the system performs. A format that often works well here is to first explain your evaluation techniques, provide their results, and then explain those results and what they say about the problem and about your approach(es) to it.
• A Conclusion, usually very brief, in which you can summarize your system and the results. In addition, this is a chance to be less scientific in your opinions about the project and a chance to put it in the larger context of larger, more general problems (such as the general vision problem or a broad subfield).

You will be graded on:

• Creativity of your project and approach.
• Quality of your implementation (including how well you evaluated your approach)
• Clarity of your paper
• More guidelines may be added here to address your specific project.

You will be turning in both an electronic copy and a hard copy for your paper rough draft (due 12/10/2013 by class start at 9:35am) and your final paper (due 12/20/2013 by class start at 9am). The electronic copies can be submitted using the webdropbox. The hard copies must be submitted in class.