Graduate

Courses

Computer Science

B552 Knowledge Based Artificial Intelligence

Credits: 3

Prerequisite(s): CSCI-B 551.

Knowledge-based methods for artificial intelligence systems: knowledge representation, organization, and application. Typical content includes: Principles of memory organization, indexing and retrieval. Memory-based, analogical, and case-based reasoning. Applications to understanding, explanation, planning, and advisory systems.

  • Course History

      Spring 2017


      Instructor: David Leake
      Time: 2:30PM-3:45PM Mon, Wed
      Location: Lindley Hall, Room 008

      Spring 2015


      Instructor: David Leake
      Time: 2:30PM-3:45PM Mon, Wed
      Location: Lindley Hall, Room 008

      Spring 2014


      Instructor: David Leake
      Time: 2:30PM-3:45PM Mon, Wed
      Location: Lindley Hall, Room 008
      Course URL (syllabus link or course homepage)
      Course File (syllabus or course advertisement)

      Spring 2013


      Instructor: David Leake
      Time: 2:30PM-3:45PM Mon, Wed
      Location: Lindley Hall, Room 008
      Course URL (syllabus link or course homepage)

      Spring 2012


      Instructor: David Leake
      Time: 2:30PM-3:45PM Mon, Wed
      Location: Lindley Hall, Room 008
      Course File (syllabus or course advertisement)
      Supplementary Description: Burgeoning availability of Web-based knowledge sources makes this an exciting time for knowledge-based AI. This course examines knowledge-based methods for AI, including knowledge representation, organization, access, and application, in the context of tasks such as story understanding, explanation, planning, problem-solving, and decision support, to provide a view of the state of the art. The course includes a semester programming project done individually or in 2-person groups.


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