Representing States & Spaces, CCN2019 Tutorial by Kim & Tim

Tim Behrens and I put together a CCN 2019 Tutorial on “Representing States and Spaces.” It was a blast: a whirlwind of RL, hippocampal/entorhinal data, philosophizing about representation learning theories, predictive representations, dimensionality reduction, generative models, factorization theories, and a four-way fight for the soul of Psychology (Thorndike / Skinner / Tolman / Harlow). Thanks to all who made it through the FOUR AND A HALF HOUR journey.

Slides are linked here: stachenfeld_behrens_ccn_tutorial_13sep2019
If you notice anything missing or incorrect, please message (email = stachenfeld[at]google[dot]com).

Some informal but very nice notes from the session were posted by Rob Gulli (https://twitter.com/rob_gulli) here:
https://docs.google.com/document/d/1baI3oN_jCkGfxJ6RZCFeAes8qi7bKxwnDi3vYFX2u7s/edit?usp=sharing

A Jupyter notebook with code for trying some of this stuff out is available on the github page for Dartmouth’s MIND 2019 Summer School from my lab there:
https://github.com/Summer-MIND/mind_2019/tree/master/tutorials/stachenfeld_lab
While you’re there, check out some of the other resources available on the page too! Lots of stuff for people interested in cognitive maps.

 


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