Pre-print of our “compositionality of intuitive functions”-paper

A pre-print of our paper “Probing the Compositionality of Intuitive Functions” is available on the Center for Brains, Minds & Machines page here

The paper contains a couple of experiments that we have run during my research stay at Harvard/MIT. These experiments tried to elicit whether human inductive biases of functions can be seen as compositional by nature.

For this, we assessed human intuitions of functions by a Gaussian Process regression framework, parameterized by three different kernels: a “one-size-fits-all” radial basis kernel, a “non-parametric all the way” spectral mixture kernel, and a compositional kernel made of different consecutive building blocks. We find that when choosing different extrapolations, when performing Markov chain Monte Carlo with people, when generating extrapolations manually as well as when deciding which functions are more predictable, people always seem to have a bias for the compositional kernel.

As compositionality speeds up intuitive inference, this might explain why participants are able to learn functions efficiently in the real world.

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s