Graduate

Courses

Computer Science

B652 Computer Models of Symbolic Learning

Credits: 3

Prerequisite(s): CSCI-B 552.

Symbolic artificial intelligence methods for learning. Inductive and explanation-based generalization. Failure-driven learning. Case-based learning. Typical content includes: Operationality of explanations and utility of learning. Goal-driven learning. Criteria for when, what, and how to learn. Learning in integrated architectures.

  • Course History

      Spring 2016


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

      Spring 2011


      Instructor: David Leake
      Time: 2:30PM-3:45PM Mon, Wed
      Location: Lindley Hall, Room 115


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