TY - GEN

T1 - Markov chain Monte Carlo with people

AU - Sanborn, Adam N.

AU - Griffiths, Thomas L.

PY - 2009/12/1

Y1 - 2009/12/1

N2 - Many formal models of cognition implicitly use subjective probability distributions to capture the assumptions of human learners. Most applications of these models determine these distributions indirectly. We propose a method for directly determining the assumptions of human learners by sampling from subjective probability distributions. Using a correspondence between a model of human choice and Markov chain Monte Carlo (MCMC), we describe a method for sampling from the distributions over objects that people associate with different categories. In our task, subjects choose whether to accept or reject a proposed change to an object. The task is constructed so that these decisions follow an MCMC acceptance rule, defining a Markov chain for which the stationary distribution is the category distribution. We test this procedure for both artificial categories acquired in the laboratory, and natural categories acquired from experience.

AB - Many formal models of cognition implicitly use subjective probability distributions to capture the assumptions of human learners. Most applications of these models determine these distributions indirectly. We propose a method for directly determining the assumptions of human learners by sampling from subjective probability distributions. Using a correspondence between a model of human choice and Markov chain Monte Carlo (MCMC), we describe a method for sampling from the distributions over objects that people associate with different categories. In our task, subjects choose whether to accept or reject a proposed change to an object. The task is constructed so that these decisions follow an MCMC acceptance rule, defining a Markov chain for which the stationary distribution is the category distribution. We test this procedure for both artificial categories acquired in the laboratory, and natural categories acquired from experience.

UR - http://www.scopus.com/inward/record.url?scp=84858791097&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84858791097&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84858791097

SN - 160560352X

SN - 9781605603520

T3 - Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference

BT - Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference

T2 - 21st Annual Conference on Neural Information Processing Systems, NIPS 2007

Y2 - 3 December 2007 through 6 December 2007

ER -