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Do you see a plausible architecture for long term planning? Putting money in my 401(k) every month to get it a few decades from now isn't something that's accessible to Q-learning, direct policy search or forward simulations. How do we learn hierarchical / semantic representations of our own actions?

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I think a similar problem needs to be solved in the language generation neural networks. While generated sentences often are formed syntactically correct, they don't make a lot of sense -- there's no over arching thought that it is trying to express. This is even more apparent when you read the subsequent sentences generated. It's clear there's no conceptual goal it's trying to convey.

In principle, adding more depth to the network can take care of that. If you are keeping track of higher and higher level abstractions, you can remember what you were saying.

But you can't remember everything, so ideally you'd also have an attention model that's capable of looking back at what you've written, and make edits. When I balance parentheses, I don't maintain a counter of how many parentheses are open, I look back at what I've written and count them.

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