| Pedagogical 
          Dimensions of Game Playing | Curriculum 
        Descant From ACM Intelligence Magazine Volume 10, Number 1, Spring 1999 ACM Press | 
| For pedagogical effectiveness, very few topics capstone the AI/Computer Science experience for a student like a programming exercise in game playing. Game Playing is one of the oldest AI topics, and yet it is worth revisiting in the context of a 3-4 week programming exercise in a one-semester course. To 
        begin, the choice of the game to be implemented should lie somewhere between 
        tic-tac-toe and chess, the former being trivial to play and the latter 
        perhaps too complicated for a short assignment. I have had moderate success 
        with versions of checkers.The choice of game is important for most of 
        the dimensions discussed below; it should be any game that is amenable 
        to the 2-person, zero-sum game algorithms. It should be a non-trivial, 
        even largely unfamiliar game. It should also allow the possibility for 
        students to think about, develop, and implement heuristics.  If 
        planned ahead of time, the completion of the exercise could culminate 
        in a tournament where not only the students' programs, but they themselves 
        may also play in it. While I have seen courses where similar tournaments 
        were held, most involve programs playing against programs. However, inserting 
        the students (or other human recruits) into the tournament brings about 
        the "human against machine" angle and serves to contextualize 
        the tournament in an AI course. All 
        put together, this represents a comprehensive task. Probably for the first 
        time for most students, they are faced with an assignment specified as 
        an "application". The potential can be stretched further by 
        specifying the addition of a graphical interface. For the web-inclined, 
        this can be a client-server implementation using CGI or written entirely 
        in Java. 
 | 
 Fall 
          1997 Summer 
          1998 Fall 
          1998 Winter 
          1998 Spring 
          1999 Summer 
          1999 Fall 
          1999 January 
          2000 Spring 
          2000 Summer 
          2000 Fall 
          2000 January 
          2001  Spring 
          2001 Spring 
          2001 | 
About Curriculum Descant
  Curriculum Descant has been a regular column in ACM's Intelligence magazine 
  (formerly published as ACM SIGART's Bulletin). The column is edited by 
  Deepak Kumar. The column features short essays on any topic relating to the 
  teaching of AI from any one willing to contribute. If you would like to contribute 
  an essay, please contact Deepak Kumar.