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  • ì   Artificial  Intelligence  

    Magy  Seif  El-­‐Nasr  

    Instructor:        Magy  Seif  El-­‐Nasr              Associate  Professor              Northeastern  University              445A  Ryder  Hall                Email:  [email protected]  

      Teaching  Assistant:    David  Batelu    

               Masters  Student                College  of  Computer  and  InformaGon  Sciences                Email:  [email protected]  


  • Outline  of  the  class  

    ì  IntroducGon  to  the  Course  

    ì  IntroducGon  to  the  teaching  staff  

    ì  Going  over  Syllabus  


  • ì   Introductions  


  • Magy  Seif  El-­‐Nasr  

    ì  Born  in  Cairo  Egypt  


    ì Wanted  to  be  a  Surgeon     (parents  are  both  medical     professors)  

  • Magy  Seif  El-­‐Nasr  

    ì  Took  a  Computer     Graphics  class  in     High  School  


    ì  That  was  1990  


    ì  Took  my  first  class  in     CS  in  high  school  

  • Magy  Seif  El-­‐Nasr  

    ì  I  declared  CS  as  my   major  at  American   University  in  Cairo   (1991)  


    ì  Directed  in  Theatre     while  studying  

  • Magy  Seif  El-­‐Nasr  

    ì  Master’s  in  CS  at  Texas  A&M  

    ì  Studied  under  Lo[i  Zadeh’s  Student  John  Yen  

  • Magy  Seif  El-­‐Nasr  

    ì  But  studied  psychology  of  emoGons  

    Build  believable     characters  

  • Magy  Seif  El-­‐Nasr  

    ì  Master’s  in  CS  at  Texas  A&M  

    ì  But  studied  psychology  of  emoGons  

    Build  believable     characters  

  • Magy  Seif  El-­‐Nasr   ì  So  I  went  to  do  my  PhD  at  Northwestern  with  

    Andrew  Ortony  and  Ian  Horswill  

    ì  To  do  this:  

    Build  believable  characters  

  • Magy  Seif  El-­‐Nasr  

    ì  Natural  Language   ì  Decision  Making    

  • Magy  Seif  El-­‐Nasr  

    ì  AI  at  Northwestern   ì  Logic   ì  Problem  Solvers    

  • Magy  Seif  El-­‐Nasr  

    ì  AI  at  Northwestern   ì  RoboGcs  

  • Magy  Seif  El-­‐Nasr   ì  But  I  was  interested  in  how  to  create  innovaGve  

    experiences  that  engage  so  many  people  of   different  ages,  and  cultures  

  • Magy  Seif  El-­‐Nasr  

    ì  PhD  in  CS  at  Northwestern  

    ì  Study  theatre  and  film  

    innova=ve     experience   engaging  a   market  

  • Magy  Seif  El-­‐Nasr  

    ì  For  Games:  everything  mabers  

    Level  Design  Concept   Texturing,  lighGng,  Framing  

    Feedback  visual/audio/hapGc   Mechanics/how  to  lead  player  

  • Magy  Seif  El-­‐Nasr   ì  For  Games:  everything  mabers  

    Sound  Physics  

    Combat  System   Leveling  up  and  progression  

  • Current  Projects  

    ì  Believable  Characters     and  InteracGve  NarraGve  

  • Current  Projects  

    ì  Game  User  Experience   ì  Games  User  Research  Methodology   ì  GUR  SIG  Steering  Commibee   ì  Game  AnalyGcs:  Data  Mining    

  • Current  Projects  

    ì  InnovaGve  Game  Design  (e.g.,  adapGve   gaming,  visualizaGon  to  sGmulate  moGvaGon)  

  • ì   INTRODUCTIONS   QuesGonnaire  #  1  

  • ì   Syllabus   Take  a  look  

  • AI  

    ì  Concepts   ì  Agents   ì  Search  Algorithms   ì  Logic  and  Inference   ì  Knowledge  RepresentaGon   ì  Planning   ì  Decision-­‐making   ì  Machine  Learning  and  Data  Mining   ì  Fuzzy  Logic  

    ì  Programming   ì  Python   ì  Data-­‐driven  programming  


  • Teaching  Method  

    ì  Website   hbp://  

    ì  Schedule:     hbp:// schedule.html  

    ì  Communica=on  and  resources:  Piazza   hbps:// home  

  • Teaching  Method  

    ì  Learning  by  doing  

    ì  All  concepts  follow  with  assignments  

    ì  Lots  of  Gme  to  apply  concepts  

    ì  Focus  on  both:     ì  criGcal  thinking,  algorithmic  thinking,  working  

    collaboraGvely,  programmer  challenges       ì  Algorithms  and  details  

  • Books  

    ì  Required:   ì  Stuart  Russell  and  Peter  Norvig.  Ar#ficial  Intelligence:  A  

    Modern  Approach,  3rd  EdiGon.  PrenGce  Hall,  2009.  

    ì  Recommended:   ì  Ken  Forbus  and  Johan  de  Kleer.  Building  Problem  Solvers.  A  

    Bradford  Book,  1993.  

  • Conduct  

    ì  No  Cell  phones  or  texts  

    ì  No  facebook,  twiber,  etc.  unless  it  is  part  of  project   work  

    ì  Late:  more  than  7  minute  late  2%  off  

    ì  AHendance:  -­‐5%  for  each  class  missed  with  no   viable  excuse  

    ì  Use  of  others’  code  or  assets  need  to  be  credited  

  • Format  

    ì  Read  chapters  assigned  before  class  

    ì  First  30  minutes  of  class:  discussion  of  the  topic  of  the  chapter  

    ì  Second  30  minutes:  concept  introducGon  

    ì  Third  30  minutes:  applicaGon  of  the  concept  and  class   assignment.  

    ì  Recommended  books  should  be  used  as  supplements  for  the   work  you  will  do  on  the  project  and  assignments  

  • Evaluation  

    Assignments:  35%     ì  Individual  Assignment  0  (5%)   ì  Individual  Assignments  1  and  2  (10%  each)   ì  Pair  Programming  Assignment  (10%)    

    Quiz:  20%  

    Project:  30%   ì  Group  (4-­‐5)   ì  5  parts:  pitch  (0%),  plan  (0%),  iteraGons  3  (10%  each),  final  

    (10%)   ì  Each  iteraGon  is  graded  –  prototype  is  graded   ì  Management  (5%)   ì  Documents  submibed  allow  you  to  go  to  the  next  stage  

  • Schedule    

  • Homework  for  Friday  

    ì  Read  Chapter  1,  for  a  quiz  on  the  topic  on  Friday.  

    ì  Sign  up  on  piazza:  hbps:// spring2013/cs41005100  

    ì  Put  in  a  post  on  piazza  a  response  to  the   introducGons  post  

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