COSC 270: Artificial Intelligence

Project 4
Fall 2017

Due: W 11/22 @ 11:59 P.M.
13 points

  1. Implement Neapolitan's algorithm for probability propagation in trees. Your implementation must be general, meaning that it must work for any tree-structured Bayesian network.

  2. Test your implementation using the example from lecture involving the patients who participated in a drug study. Implement this test as example1. It should instantiate the evidence that the doctor has encountered a cured patient and print the probability that the patient was part of the drug study.

  3. Test your implementation using Neopolitan's “cheating spouse example” (Section 6.2.2), which you can find on Canvas. Implement this test as example2. It should instantiate the evidence that the spouse is reported seen dining with another and print the probability that a strange man/lady calls on the phone.

  4. For both examples, the implementation should print the entire state of all of the nodes in the network before initialization, after initialization, and after instantiation.

Instructions for Electronic Submission

The name of the file containing your Lisp functions must be named main.lisp. In a file named HONOR, provide the following information:

In accordance with the class policies and Georgetown's Honor Code,
I certify that, with the exceptions of the course materials and those
items noted below, I have neither given nor received any assistance
on this project.

When you are ready to submit your project, create the zip file for uploading by typing:

$ zip main.lisp HONOR
Upload to Autolab. You can submit to the compile check p4c five times. You can submit your assignment p4 fives times.

Plan B

If Autolab is down, upload your zip file to Canvas.

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