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SUBJECT TO CHANGE!! Last updated 8/27/2010 Homework and Labs are due ON THE DATE where the homework or lab is linked.
Quick links to clarifying discussions
<table border=1> <tr> <th width=20>Date</th><th>Topic</th><th>Reading</th><th>Homework</th><th>Labs</th>
<tr> <th>Tues. 8-31</th> <td>Introduction to AI & Class Policies</td> <td>Syllabus, Chapter 1</td> <td> </td> <td> </td>
<tr> <th> Thurs. 9-2</th> <td> Potential Fields and PD Controllers </td> <td> Potential Fields, PD Controllers, Section 25.6.1</td> <td> MATLAB Tutorial</td> <td></td>
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<tr> <th> Tues. 9-7</th> <td> Agents </td> <td> Chapter 2, Another view of agents, Intelligence Without Representation</td> <td>BZFlag Tutorial Homework </td> <td></td>
<tr> <th>Thurs. 9-9</th> <td>Uninformed Search Review, Probabilistic Roadmaps</td> <td>Sections 3-1-3.4, page 993, Wikipedia PRMs</td> <td>Agents Homework</td> <td> </td>
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<tr> <th>Tues. 9-14</th> <td>Informed Search </td> <td>Sections 3.5-3.6, Example </td> <td>Uninformed Search Homework</td> <td> </td>
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<th>Thurs. 9-16</th> <td><b> new </b> Wikipedia probabilistic road maps <b>new</b>Local Search</td> <td>Sections 4.1-4.2 (stop on page 132 when you reach the paragraph “For many problems…”)</td> <td>PRM Homework – modified Sept 14</td> <td></td>
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<tr> <th>Tues. 9-21</th> <td>Probability Spaces and Axioms, Random Variables</td> <td>Section 13.1-13.2, Wikipedia Random Variable (stop at “Functions of RVs”), Wikipedia Probability Space (stop at “General Case”), Wikipedia Sigma Algebra (stop at “Generated Sigma Algebra”)</td> <td> Local Search Homework – modified Sept 14 </td> <td></td>
<tr> <th>Thurs. 9-23</th> <td>Joint Distributions, Marginal Distributions, Conditional Distributions</td> <td>Sections 13.3-13.4, Wikipedia Marginal Distribution</td> <td></td> <td>Potential Fields Lab</td>
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<tr> <th> Tues. 9-28 </th> <td> Bayes Rule</td> <td> 13.5 </td> <td> Genetic Algorithms Homework</td> <td> </td>
<tr> <th> Thurs. 9-30 </th> <td> Bayes Rule continued, MAP Estimators, Maximum Likelihood</td> <td> Wikipedia Monty Hall Problem, Wikipedia MAP estimators (stop at “Criticism”) </td> <td> Bayes Rule Homework</td> <td> </td>
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<tr> <th>Tues. 10-5</th> <td>Markov Processes, Conditional Independence, and the Bayes Filter</td> <td>Parameter Estimation, Section 15.1 and 15.2 through page 573 and a class handout</td> <td>Second Bayes Rule Homework</td> <td></td>
<tr> <th>Thurs. 10-7</th> <td>Catch-up and Exam 1 Review</td> <td>Exam 1 will cover through Bayes Rule and will not cover the Bayes Filter</td> <td></td> <td>Search Lab</td>
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<tr> <th>Tues. 10-12</th> <td>No class — Mike Travel</td> <td></td> <td></td> <td></td>
<tr> <th>Thurs. 10-14</th> <td>No class — Mike Travel</td> <td></td> <td></td> <td></td>
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<tr> <th>10/15-10/18</th> <td>Exam 1 in Testing Center</td> <td></td> <td></td> <td></td>
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<tr> <th>Tues. 10-19</th> <td>Nonparametric Bayes Filters: the Grid Filter</td> <td>Class handout & Grid Filter in MATLAB</td> <td></td> <td></td>
<tr> <th>Thurs. 10-21</th> <td>Parametric Filter: Estimating Means and Dynamic System Models</td> <td>Wikipedia Kalman Filter section on Underlying Dynamic System Model</td> <td>Grid Filter Homework easy difficulty rating, but plan some on spending enough time to do all of the variations</td> <td></td>
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<tr> <th>Tues. 10-26</th> <td>Kalman Filter</td> <td>15.4</td> <td></td> <td>Multiagent Lab</td>
<tr> <th>Thurs. 10-28</th> <td>Kalman Filter continued <s>and Exam 1 Discussion</s></td> <td>15.4</td> <td>Kalman Filter Homework moderate difficulty rating. Plan some extra time to figure out what the dots and ellipses mean.</td> <td></td>
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<tr> <th>Tues. 11-2</th> <td>Chain Rule, Conditional Independence, Bayesian Networks and NEW Exam 1 Discussion</td> <td>Sections 14.1-14.2 and Conditional Independence Example</td> <td>Second Kalman Filter Homework high difficulty rating. Plan some extra time and consider group work.</td> <td></td>
<tr> <th>Thurs. 11-4</th> <td>Bayesian Networks: AND, OR, Temporal Inference, Naive Bayes</td> <td>Section 14.3 through page 519, NLP Naive Bayes (pg 2), and CS 478 Naive Bayes tutorial</td> <td>Bayesian Nets Homework moderate difficulty rating. There are a lot of things to compute. This would be a good homework to consider for group work.</td> <td></td>
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<tr> <th>Tues. 11-9</th> <td><s>Preferences, utility, expected utility</s></td> <td><s>Sections 16.1-16.4 (stop reading after section 16.3.2)</s></td> <td></td> <td></td>
<tr> <th>Thurs. 11-11</th> <td>Preferences, utility, expected utility</td> <td>Sections 16.1-16.4 (stop reading after section 16.3.2)</td> <td></td> <td></td>
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<tr> <th>Tues. 11-16</th> <td>Making complex decisions: representations and discounting</td> <td>Sections 17.1-17.2</td> <td></td> <td>Kalman Filter Lab</td>
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<tr> <th>Thurs. 11-18</th> <td>Exam 2 Review</td> <td>Exam 2 covers through the expected utility</td> <td>Utility Theory Homework moderate difficulty rating</td> <td></td>
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<tr> <th>11/19-11/22</th> <td>Exam 2 in Testing Center</td> <td></td> <td></td> <td></td>
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<tr> <th>Tues. 11-23</th> <td>No Class – Friday Instructional Schedule</td> <td></td> <td></td> <td></td>
<tr> <th>Thurs. 11-25</th> <td>No Class – Thanksgiving</td> <td></td> <td></td> <td></td>
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<th>Tues. 11-30</th> <td>Making complex decisions: The Value Iteration Algorithm</td> <td>Section 17.2, ValueIteration MATLAB Code</td> <td></td> <td></td>
<tr> <th>Thurs. 12-2</th> <td>Games (Lanny Lin substitute teacher)</td> <td>Sections 5.1-5.3</td> <td></td> <td></td>
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<tr> <th>Tues. 12-7</th> <td>Making complex decisions: The Policy Iteration Algorithm</td> <td>Section 17.3</td> <td>Games Homework moderate difficulty rating. This would be a good homework for group work.</td> <td></td>
<tr> <th>Thurs. 12-9</th> <td>Final Exam Review</td> <td>The final is comprehensive.</td> <td>FYI, do not turn this in. The key is posted on the window of 2244 TMCB. Sequential Choice Homework high difficulty rating. Plan quite a bit of extra time because there are a lot of things to compute. Consider group work.</td> <td>Tournament Lab (Subject to Change)</td>
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<tr> <th>12/13-12/17 </th> <td>Final Exam in Testing Center</td> <td></td> <td></td> <td></td>
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Things that I've assigned in the past, but not this semester.
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