CS343H: Honors Artificial Intelligence -- Spring 2015: Assignments Page

Assignments for Honors Artificial Intelligence (cs343H)

Week 0: Introduction (8/31)

Readings: Due 9:30 am on Thursday, 8/31 (i.e. BEFORE THE FIRST CLASS SESSION)

Read the 2016 AI100 Study Panel Report

Write a 500-word response to one or more of the sections indicating your reactions (e.g. agreement, disagreement, musings, etc.)

Send your response as ASCII text (not encoded in any way) to pstone@cs.utexas.edu, jphanna@cs.utexas.edu, alexzhao@cs.utexas.edu, and rohan@cs.utexas.edu with subject: "class readings 8/31".

Programming: Due 9:30am on Tuesday, 9/5

If you don't have a CS UNIX account (e.g. because you're a non-CS major), sign up for a temporary account IMMEDIATELY! It will take several days for the account to be activated. Also, please be aware that the account will expire and completely disappear two weeks into the summer semester.

Programming: Due 9:30am on Thursday, 9/7

Python tutorial. This tutorial should be submitted with the assignment name cs343-0-tutorial using these submission instructions.

Week 1: Agents (9/5,7)

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook - Chapter 1 through the end of Section 1.1 (Rest of chapter 1 is optional - I recommend at least skimming it)

Textbook - Chapter 2

For your response, select one real or imaginable agent not discussed in class or in the readings, give a PEAS description of the task environment, and characterize it in terms of the properties listed in Section 2.3.2.

Send your response as ASCII text (not encoded in any way) to pstone@cs.utexas.edu, jphanna@cs.utexas.edu, alexzhao@cs.utexas.edu, rohan@cs.utexas.edu with subject: "class readings for 9/5".

As indicated on the course overview page, your response should be well-thought-out, coherent, and concise. Quality of written expression will be a factor in the grading (use full sentences). Short, to-the-point answers are preferred. For full credit, your email should be sent by 5pm on Monday, 9/4.

Self-introduction: Due Tuesday at 9:30am

Post a self-introduction and at least one other item to the piazza site. If nothing else, you may post your reading response. But feel free to post questions, comments, or reactions to other peoples' posts instead or in addition.

EdX Homework 1: Due 11:59pm on Tuesday, 9/19

Complete the search assignment on EdX (Homework 1).

Week 2: Search (9/12,14)

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook - Chapter 3

Respond to the readings by email

Programming: Due 9:30am on Thursday, 9/28

Search assignment. This search assignment should be submitted with the assignment name cs343-1-search using these submission instructions. Details regarding what to submit are inside the assignment's description.

Week 3: Constraint Satisfaction Problems and Local Search (9/19,21)

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook - Chapter 6

Textbook - Sections 4.1 and 4.2 (Rest of chapter 4 is optional - I recommend at least skimming it)

Respond to the readings by email

EdX Homework 2: Due 11:59pm on Tuesday, 9/26

Complete the constraint satisfaction assignment on EdX (Homework 2).

Week 4: Adversarial Search, Utilities (9/26,28)

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Chapter 5 through the end of Section 5.5 (Rest of chapter 5 is optional - I recommend at least skimming it)

Textbook Chapter 16 through the end of Section 16.3

Respond to the readings by email.

EdX Homework 3: Due 11:59pm on Tuesday, 10/3

Complete the multi-agent search assignment on EdX (Homework 3).

Programming: Due 9:30am on Thursday, 10/12

Multiagent assignment. This multiagent assignment should be submitted with the assignment name cs343-2-multiagent using these submission instructions. Details regarding what to submit are inside the assignment's description.

Week 5: Markov Decision Processes (10/3,5)

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Chapter 17 through the end of Section 17.3

Sutton and Barto Chapters 3 and 4.

Respond to the readings by email.

EdX Homework 4: Due 11:59pm on Tuesday, 10/10

Complete the Markov decision process assignment on EdX (Homework 4).

Week 6: Reinforcement Learning (10/10,12)

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Chapter 21

Sutton and Barto Sections 6.1, 6.2, and 6.5.

Respond to the readings by email.

EdX Homework 5: Due 11:59pm on Tuesday, 10/17

Complete the reinforcement learning assignment on EdX (Homework 5).

Programming: Due 9:30am on Thursday, 11/2

Reinforcement learning assignment. This assignment should be submitted with the assignment name cs343-3-reinforcement using these submission instructions. Details regarding what to submit are inside the assignment's description.

Week 7: Bayes' Nets: Representation and Inference (10/17,19)

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

If you need a review of Probability, Textbook Chapter 13 through the end of 13.5 (optional). I suggest at least skimming it to familiarize yourselves with the book's notation.

Textbook Chapter 14 through the end of Section 14.5

Textbook Section 14.7. (You can skim this part - it is mainly to address questions about what alternatives there are to probabilistic models of uncertainty).

Respond to the readings by email.

EdX Homework 6: Due 11:59pm on Tuesday, 10/31

Complete the Bayes' net assignment on EdX (Homework 6).

Week 8: Midterm (10/24,26)

Jump to the resources page.

Review on Tuesday, In-class Mid-term on Thursday

Complete the midterm course evaluation survey by Monday night at 5pm. Either include your name in the response (optional), or send us a screenshot of the submission screen to credit credit for this week's "reading assignment."

Week 9: (Hidden) Markov Models, Particle Filters, and VOI (10/31,11/2):

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Chapter 15 through the end of Section 15.3.

Textbook Section 15.4 is optional (I recommend at least skimming it)

Textbook Chapter 15.5

Textbook Sections 16.5 and 16.6

Respond to the readings by email.

EdX Homework 7: Due 11:59pm on Tuesday, 11/7

Complete the Bayes' net sampling, VOI, and particle filtering assignment on EdX (Homework 7).

Programming: Due 9:30am on Thursday, 11/9

Bayes assignment. This assignment should be submitted with the assignment name cs343-4-bayes using these submission instructions. Details regarding what to submit are inside the assignment's description.

Programming: Due 9:30am on Tuesday, 12/5

Capture the flag contest

Week 10: Naive Bayes and Perceptrons (11/7,9):

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Chapter 18 through the end of Section 18.2

Skim Sections 18.3, but pay attention to the definition of overfitting in 18.3.5.

Section 18.4

Section 18.5 is optional

Section 18.6 except Sections 18.6.2 and 18.6.4

Sections 18.6.2 is optional (18.6.4 is assigned next week)

Textbook Chapter 20 through the end of Section 20.2

You can skim 20.2.3 if you're not comfortable with reasoning about continuous distributions (e.g. Gaussians).

20.2.5 is just an overview without all the details - do your best.

Textbook Section 20.3 is optional

Respond to the readings by email.

EdX Homework 8: Due 11:59pm on Tuesday, 11/14

Complete the Naive Bayes and Perceptron assignment on EdX (Homework 8).

Programming: Due 9:30am on Tuesday, 11/21

Ghostbusters assignment. This assignment should be submitted with the assignment name cs343-5-ghostbusters using these submission instructions. Details regarding what to submit are inside the assignment's description.

Week 11: Deep Learning (11/14,16):

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Section 18.6.4

Textbook Section 18.7

Watch the Berkeley course Deep Learning I lecture, starting at minute 27

Watch the Berkeley course Deep Learning II lecture (parts of minutes 5-15 are review from the first lecture)

Respond to the readings and videos by email.

EdX Homework 9: Due 11:59pm on Tuesday, 11/28

Complete the Neural networks and Optimization assignment on EdX (Homework 9).

Week 12: SVMs, Kernels, and Clustering (11/21):

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Sections 18.8, 18.9, and 18.11.

Section 18.10 is optional.

Respond to the readings by email.

Programming: Due 9:30am on Thursday, 12/7

Classification assignment. This assignment should be submitted with the assignment name cs343-6-classification using these submission instructions. Details regarding what to submit are inside the assignment's description.

Week 13: Classical Planning (11/28,30):

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Chapter 10. (Focus on Sections 10-10.3)

Respond to the readings by email.

Week 14: Philosophical Foundations (12/5,7):

Jump to the resources page.

Readings: Due Tuesday (email response due Monday at 5pm)

Textbook Chapters 26 and 27

Respond to the readings by email. Please include in your response if/how your thoughts about any of the questions considered in the chapters have changed since before you took the course.

Final Exam: December 18th from 2-5pm

The final exam for this class will be on December 18th from 2-5pm.

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