Brian R. Christian
2010
Using category structures to test iterated learning as a method for identifying inductive biasesdoi.orgPDF
Cognitive Science 32(1):68--107, 2010
Abstract Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases—assumptions about the world that make ...
2006
Revealing priors on category structures through iterated learningPDF
Proceedings of the 28th Annual Conference of the Cognitive Science Society, 2006
We present a novel experimental method for identifying the inductive biases of human learners. The key idea behind this method is simple: we use participants' re- sponses on one trial to generate the stimuli they see on the next. A theoretical analysis of this ``iterated learn- ...MORE ⇓
We present a novel experimental method for identifying the inductive biases of human learners. The key idea behind this method is simple: we use participants' re- sponses on one trial to generate the stimuli they see on the next. A theoretical analysis of this ``iterated learn- ing'' procedure, based on the assumption that learners are Bayesian agents, predicts that it should reveal the inductive biases of the learners, as expressed in a prior probability distribution. We test this prediction through two experiments in iterated category learning.