Abstract

Different representation languages are useful for capturing different inductive biases. What is the language that best captures human inductive biases? I will present several models and studies which suggest that human knowledge is mentally represented in a logical language, and that human learning can be characterized in terms of probabilistic inference over these logical representations. The applications presented will include category learning, relational learning, and one-shot learning.

Venue, Date, and Time

Venue: GHC 6115

Date: Monday, November 2, 2009

Time: 12:00 noon