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IIRC there is evidence rats replay their experiences, sped up, while they are asleep. Dreaming may be something else entirely though, because my dreams aren't a

IIRC there is evidence rats replay their experiences, sped up, while they are asleep. Dreaming may be something else entirely though, because my dreams aren't anything like my memories of the day before. Artificial neural networks can "dream" by predicting what frame it will see next. This is a really cool technique. They've shown slightly blurry videos of atari games being played that comes entirely from the network's dream. With no interaction with the game at all. You can even train the reinforcement learning on the dream sequences and improve it's performance. But this also doesn't seem quite like what human dreams are. Human dreams are wild and unrealistic, while the NN dreams try to match the training data as closely as possible.

chris_st 10y ago
Quite a few of my dreams seem to be slightly scary situations (dangerous behavior of other drivers while I'm driving, for example). This makes me think that we have a "scenario generation" engine as part of our brains, and so we're being presented with novel experiences (often "wild and unrealistic") to react to. So this seems to be a pretty big step beyond the idea of presenting previously seen situations (which sounds like a really good first step, of course).
glial 10y ago
> IIRC there is evidence rats replay their experiences... https://en.wikipedia.org/wiki/Hippocampal_replay https://en.wikipedia.org/wiki/Hippocampal_replay for anyone that's interested.
Jabbles 10y ago
You can even train the reinforcement learning on the dream sequences and improve it's performance. I'm not sure how that would work. Surely you'd be overfitting on your training set by definition?
- Houshalter 10y ago
  Reinforcement learning has a problem in that it gets very little labelled data. You may have a million frames, but the only label is the score. Which may only change a few times per game. Training the net to predict the next frame is sort of unsupervised learning. It can learn the rules of the game without score information at all. The second thing is that RL is different than prediction. Even if you can predict the next frame exactly, finding the optimal set of moves is still a hard problem. The algorithm needs to learn more than just predicting what will happen, but also what the optimal action is in every situation. That is something that can be practiced in simulations, or "dreams".

chris_st 10y ago

Quite a few of my dreams seem to be slightly scary situations (dangerous behavior of other drivers while I'm driving, for example). This makes me think that we have a "scenario generation" engine as part of our brains, and so we're being presented with novel experiences (often "wild and unrealistic") to react to. So this seems to be a pretty big step beyond the idea of presenting previously seen situations (which sounds like a really good first step, of course).

glial 10y ago

> IIRC there is evidence rats replay their experiences... https://en.wikipedia.org/wiki/Hippocampal_replay https://en.wikipedia.org/wiki/Hippocampal_replay for anyone that's interested.

Jabbles 10y ago

You can even train the reinforcement learning on the dream sequences and improve it's performance. I'm not sure how that would work. Surely you'd be overfitting on your training set by definition?

Houshalter 10y ago
Reinforcement learning has a problem in that it gets very little labelled data. You may have a million frames, but the only label is the score. Which may only change a few times per game. Training the net to predict the next frame is sort of unsupervised learning. It can learn the rules of the game without score information at all. The second thing is that RL is different than prediction. Even if you can predict the next frame exactly, finding the optimal set of moves is still a hard problem. The algorithm needs to learn more than just predicting what will happen, but also what the optimal action is in every situation. That is something that can be practiced in simulations, or "dreams".