The theory of chunking developed out of George Miller’s study of working memory in humans (opens in new tab). It can be used to explain how humans can effectively exceed the capacity of their working memory (7 plus or minus 2 items) by organizing (recoding) the items into a number of groups (chunks). This project explores whether Neural Networks can process relatively large structures of items using a chunking approach, where each chunk of items is a small structure encoded into a Tensor Product Representation (TPR).