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Regrading:

If you feel that your homework was not graded correctly, you should return it to me, along with a written explanation of the error. I will evaluate this explanation and award any necessary points.

A python script for fetching random web pages can be found here . Feel free to modify or improve upon it.


(12/11) Here are solutions to the extra probability and utility problems I sent out.

Here are the solutions to midterm 2.

A list of potential topics for midterm 2 can be found here

A sample midterm can be found here . (note: ignore the questions about probability and utility - we'll get to that after the midterm.)

A version with answers can be found here.

Update 10/27: Here is another FOL problem to practice on.


Here are the solutions to midterm 1.

A sample midterm can be found here . (note: ignore question 6 - we haven't covered adversarial search yet.)

A version with answers can be found here.

A list of potential midterm topics can be found here .

Lectures and associated readings:

Date Topic Associated Reading Slides
August 25 Lecture 1: Introduction. What is AI? R & N: 1.1 pp 1-4, 26.1-2: pp 947-958 Full Size Printable
August 30 Lecture 2: Intro to Python Dive Into Python Chapters 2,3,6. Full Size Printable
September 1 Lecture 3: Agents and Environments R & N: Chapter 2: pp 32-58 Full Size Printable
September 6 Lecture 4: More Python Dive Into Python Chapters 4,5,8. Full Size Printable
September 8 Lecture 5: Search I: BFS, DFS, IDS R & N: 3.1-3.5 pp 59-83 Full Size Printable
September 13 Lecture 6: Search II: Greedy Search, A* R & N: 4.1-4.2 pp 94-109 Full Size Printable
September 15 Lecture 7: Constraint Satisfaction, Branch and Bound R & N: 5.1-5.2 pp 137-150 Full Size Printable
September 20 Lecture 8: Local Search and Genetic Algorithms R & N: 4.3 pp 110-119 Full Size Printable
September 22 Lecture 9: Project 1 discussion Project 1 Full Size Printable
September 27 Lecture 10: Introduction to Knowledge Representation R & N: 7.1-7.5: pp 194-220 Full Size Printable
September 29 Guest Lecture N/A
October 4 Midterm 1 N/A
October 6 Lecture 12: First-order Logic R & N: 8.1-8.3: pp 240-258 Full Size Printable
October 11 Lecture 13: Inference, Rule-based Systems R & N: 9.1-9.6: pp 272-300 Full Size Printable
October 13 No class
October 18 Lecture 14: Decision Trees R & N 18.1, 18.2 Full Size Printable
October 20 Lecture 15: Ontologies Protege Tutorial
Ontology Development 101
Full Size Printable
October 25 Lecture 15: More Ontologies, Project 2 discussion Tutorial on using OWL with Protege
Ontology Development 101
Full Size Printable
October 27 Lecture 16: Planning R & N: 11.1-11.3: pp 375-395 Full Size Printable
November 1 Midterm 2
November 3 Lecture 17: Introduction to Probability R & N 13.1-13.6: pp 462-481 Full Size Printable
November 8 Lecture 18: Bayesian Networks R & N 14.1, 14.2: pp 492-499. Full Size Printable
November 10 Lecture 19: Bayesian Learning R & N 20.1: pp 712-716 Full Size Printable
November 15 Lecture 20: Introduction to Machine Learning R & N: 20.1, 21.1: 712-716, 763-765 Full Size Printable
November 17 Project 3 discussion Project 3
November 22 Lecture 21: Utility and Value of Information R & N 16.1-16.3, 16.6: pp 584-591,600-603
Full Size Printable
November 29 Lecture 22: MDPs R & N: 17.1-17.3: pp 613-625 Full Size Printable
December 1 Lecture 23: Neural Networks R & N: 749-752 Full Size Printable
December 5 Lecture 24: Neural Networks, summary n/a Full Size Printable

Sample code

Sample code from the intro to python lecture


Links


Protege Resources

GA/GP readings

Python links

AIMA links