Computer Science 470

Introduction to Artificial Intelligence

Fall 2010

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<h3> Course Goals </h3>
At the end of this course, and for at least one year after, you should be able to:
<table border="3" summary="Goals for CS470">
Recognize an AI problem, no matter the source of the problem
	<li> Business</li> 
	<li> Medicine </li>
	<li> Gaming</li>
	<li> Robotics </li>
	<li> Research, etc. </li>
<tr><td> Identify the component elements of the problem:
	<li> Does it require basic control? </li>
	<li> Does it involve uncertain reasoning? </li>
	<li> Does it have a simple goal, sophisticated utility, or multiple attributes? </li>
	<li> Does it require sequential choice/planning?</li>
	<li> How many of decision makers are involved?</li>
<tr> <td>Formalize the problem in a way that is amenable to a solution.
	<li> Representation or reaction </li>
              <li> PEAS and the nature of environment </li>
	<li> CSA, states, and sequencing </li>
	<li> Random variables, pdfs, cdfs, joint distributions </li>
	<li> Values </li>
<tr> <td>Recall the names and use for different classes of algorithms
	<li> Uninformed, informed, constraint-satisfaction, and hill-climbing search </li>
	<li> Markov processes, Bayes rule, Bayes nets, HMMs, grid filters, and Kalman filters </li>
	<li> Expected utility theory and multi-attribute utility theory </li>
	<li> Sequential choice under uncertainty: value and policy iteration </li>
	<li> Game theory </li>
<tr><td> Implement several algorithms using the specifications from a book
<tr><td> Determine whether your solution is correct and what to do if it's not
<tr><td> Value the quality of a well-communicated solution
cs-470fl10/start.txt · Last modified: 2014/12/09 15:51 by ryancha
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