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Date: Wed, 20 Nov 1996 22:16:08 GMT
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<head><TITLE>CPS 296 - SPRING 1997 </TITLE><LINK REV="made" HREF="mailto:mlittman@cs.duke.edu"></head><body> <p><center><TABLE BORDER=10 CELLSPACING=5 > <TR> <TD align=center colspan=4> <h1>CPS296</h1> </TD> </TR> <TR></TR> <TR> <TD></TD> <TD ALIGN=center> <H1>Spring 1997</H1> </TD> <TD align=center></TD> <TD ALIGN=center> <H1>Advanced Topics in Artificial Intelligence</H1> </TD> </TR></TABLE></center><p><center>[ <!WA0><A href="#background"> Background </A> |<!WA1><A href="#grading"> Grading </A> |<!WA2><A href="#outline"> Outline </A> ]</center><hr><a name="background"><h2> Background </h2>We will review some advanced topics in artificial intelligence:planning, reasoning under uncertainty, decision making, vision,robotics, reinforcement learning. Topics will be almost entirelydisjoint from those of CPS270, so students that have taken CPS270 arewelcome to take this class as well.<h3> Instructor </h3><!WA3><A href="http://www.cs.duke.edu/~mlittman">Michael L. Littman</a><ul><li>Office: D209 LSRC<li>Phone: 660-6537<li>Email: <!WA4><ahref="mailto:mlittman@cs.duke.edu">mlittman@cs.duke.edu</a><li>Office hours: TBA</ul><h3> Meeting Times </h3>MWF 10:30 D243<h3> Textbook </h3>Stuart Russell and Peter Norvig. (1995). <em>ArtificialIntelligence: A Modern Approach</em>. Prentice-Hall, EnglewoodCliffs, New Jersey. (<!WA5><ahref="http://http.cs.berkeley.edu/~russell/aima.html">book homepage</a>) <p>Note that Curry Guinn used the same book in <!WA6><ahref="http://www.cs.duke.edu/~cig/cps170.html">CPS170</a> last year.From what I can tell, the overlap between the two courses (after theinitial introductory material) is quite small.<h3>Prerequisites</h3>I will assume that students are familiar with programming (anylanguage), algorithm analysis (big O notation and the like at thelevel of CPS130), and simple calculus (derivatives).<hr><h2> <A NAME="grading"> Grading </h2>Class grade will be based on:<UL><LI> written homework assignments (20%),<LI> programming projects (20%),<LI> two in-class exams (30%), and<LI> a final exam (30%).</UL><hr><A NAME="outline"><h2>Outline</h2>I'm going to follow the suggested syllabus in the textbook for aone-semeter course with concentration on vision and robotics. Hereare the chapters we'll cover.<ul> <li> I. Artificial Intelligence <ul> <li> 1. Introduction <li> 2. Intelligent Agents </ul> <li> II. Problem Solving <ul> <li> 3. Solving Problems by Searching <li> 4. Informed Search Methods </ul> <li> III. Knowledge and Reasoning <ul> <li> 6. Agents that Reason Logically <li> 7. First-Order Logic </ul> <li> IV. Acting Logically <ul> <li> 11. Planning <li> 13. Planning and Acting </ul> <li> V. Uncertain Knowledge and Reasoning <ul> <li> 14. Uncertainty <li> 15. Probabilistic Reasoning Systems <li> 16. Making Simple Decisions <li> 17. Making Complex Decisions </ul> <li> VI. Learning <ul> <li> 20. Reinforcement Learning </ul> <li> VII. Communicating, Perceiving, and Acting <ul> <li> 24. Perception <li> 25. Robotics </ul></ul><hr><address>Last modified: Mon Nov 18 09:56:11 EST 1996by Michael Littman, mlittman@cs.duke.edu</font></body>⌨️ 快捷键说明
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