COSC 574: Automated Reasoning

Project 4
Spring 2016

Due: M 5/2 @ 11:59 PM
20 points

For this project, you will select a method for logical or uncertain reasoning from the primary literature, implement it, and informally instruct the class on the method. You must demonstrate that your implementation of the method runs on at least two sample problems. The class will read one or two of the key papers detailing your chosen method in advance of your class discussion.

• approximate inference methods for Bayesian networks
• KBMC approaches to first-order probabilistic logics (e.g., MLNs)
• Lifted inference for FOPL (e.g., FOVE)

The method you choose must be sufficiently different from the previous projects. For example, implementing a variation of linear resolution is not adequate.

You must identify a method and article(s) by April 13. Plan on discussing your method with the class on April 25 or April 27. The method implementation is worth 12 points, the sample problems are worth 3 points, and your class discussion is worth 5 points.

In the header comments in at least the main file of your project, provide the following information:

//
// Name
// E-mail Address
// Platform: Windows, OS X, Linux, etc.
// Language/Environment: gcc, g++, java, ruby, python
//
// In accordance with the class policies and Georgetown's Honor Code,
// I certify that, with the exceptions of the class resources and those
// items noted below, I have neither given nor received any assistance
// on this project.
//