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B551 Elements of Artificial Intelligence

Credits: 3

Prerequisite(s): CSCI-C 343.

Introduction to major issues and approaches in artificial intelligence. Principles of reactive, goal-based, and utility-based agents. Problem-solving and search. Knowledge representation and design of representational vocabularies. Inference and theorem proving, reasoning under uncertainty, and planning. Overview of machine learning.

Spring 2018


Instructor: Hasan Kurban
Time: 4:00PM-5:15PM Tue, Thu
Location: FA102

  • Course History

      Fall 2017


      Instructor: David Crandall
      Time: Multiple Times
      Location: Multiple Locations

      Fall 2016


      Instructor: David Crandall
      Instructor: Sven Bambach
      Time: Multiple Times
      Location: Multiple Locations
      Course File (syllabus or course advertisement)


      Instructor: Tor Lattimore
      Time: 4:00PM-5:15PM Tue, Thu
      Location: FA102

      Spring 2016


      Instructor: Sriraam Natarajan
      Time: 7:15PM-8:30PM Mon, Wed
      Location: FA102

      Fall 2015


      Instructor: David Leake
      Time: 4:00PM-5:15PM Tue, Thu
      Location: Informatics East, Room 150


      Instructor: David Crandall
      Time: 8:00PM-9:15PM Tue, Thu
      Location: Woodburn Hall, Room 111

      Fall 2014


      Instructor: David Leake
      Time: 4:00PM-5:15PM Tue, Thu
      Location: Ballantine Hall, Room 005

      Fall 2013


      Instructor: David Leake
      Time: 4:00PM-5:15PM Tue, Thu
      Location: Woodburn Hall, Room 004
      Course URL (syllabus link or course homepage)

      Fall 2012


      Instructor: Kris Hauser
      Time: 11:15AM-12:45PM Tue, Thu
      Location: Informatics East, Room 130

      Fall 2011


      Instructor: Kris Hauser
      Time: 4:00PM-5:15PM Tue, Thu
      Location: Ballantine Hall, Room 217
      Course URL (syllabus link or course homepage)
      Supplementary Description: Programming projects will be in Python rather than LISP.