Here is a recent Facebook research paper that addresses the problem I believe this paper is intended to solve.<p>Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
<a href="http:&#x2F;&#x2F;arxiv.org&#x2F;pdf&#x2F;1502.05698v6.pdf" rel="nofollow">http:&#x2F;&#x2F;arxiv.org&#x2F;pdf&#x2F;1502.05698v6.pdf</a><p>This recent paper is an algorithm to solve simple question answering from the context of a conversation... like the ones in the older paper... for instance.<p>John is in the playground.<p>Bob is in the office.<p>Where is John? A:playground<p>I believe a traditional LSTM RNN would have likely cleared the information about John from from it&#x27;s long short term memory vector.  Whereas you would still have access to the information about John in a stack.<p>fta: &quot;Since the machine can essentially learn how to operate its memory, it can learn how to program itself by producing sequences of instructions.&quot;