Danijar Hafner 2
TalkRL: The Reinforcement Learning Podcast
The Importance of Hierarchies in Abstract Planning
Do you see future directors having more levels of management to span to higher levels of temporal obstruction? So that's a very good question. I think there are two perspectives on this. One is, yes, you just want a deep hierarchy but maybe these hierarchies can actually be a bit more implicit than that. Maybe we don't want like a fixed number of 10 levels. And what if we can train dynamics models such that some of the features just change less often than others? It seems like a pretty compelling idea. But it's a big open question how to actually learn that and use that for abstract planning.
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