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A preference ordering on lotteries over outcomes is called geometrically rational if there exists some probability distribution  over interval valued utility functions on outcomes such that  if and only if .

How does this work with Kelly betting? There, aren't the relevant utility functions going to be either linear or logarithmic in wealth?

Similarly, the next iteration of this should definitely ask about The Inside View.

Would have been good to ask about that and also mine it for resources.

Re: future iterations, I'm not sure. On one hand, I think it's kind of bad for this kind of thing to be run by a person who stands to benefit from his thing ranking high on the survey. On the other hand, I'm not sure if anyone else wants to do it, and I think it would be good to run future iterations.

If anyone does want to take it over, please let me know. I'm not sure how many would be interested in doing that (maybe grantmaking orgs?), but if there are multiple such people it would probably be good to pick a designated successor. I should say that I reserve the right to wait until next year to make any sort of decision on this.

I didn't want to name and shame lower-ranked entries, but if you go to the github and run the code you can see the whole ranked list for each category you're interested in - just have to uncomment the relevant part of the script.

My guess is that it's also because conversations are less optimized (being done on the fly) and maybe harder to access. It's still the case that people getting into alignment found them "very" useful on average, which seems like high praise to me.

One reason that I doubt this story is that "try new things in case they're good" is itself the sort of thing that should be reinforced during training on a complicated environment, and would push towards some sort of obfuscated manipulation of humans (similar to how if you read about enough social hacks you'll probably be a bit scammy even tho you like people and don't want to scam them). In general, this motivation will push RL agents towards reward-optimal behaviour on the distribution of states they know how to reach and handle.

Actually I'm being silly, you don't need ring signatures, just signatures that are associated with identities and also used for financial transfers.

Note that for this to work you need a strong disincentive against people sharing their private keys. One way to do this would be if the keys were also used for the purpose of holding cryptocurrency.

Here's one way you can do it: Suppose we're doing public key cryptography, and every person is associated with one public key. Then when you write things online you could use a linkable ring signature. That means that you prove that you're using a private key that corresponds to one of the known public keys, and you also produce a hash of your keypair, such that (a) the world can tell you're one of the known public keys but not which public key you are, and (b) the world can tell that the key hash you used corresponds to the public key you 'committed' to when writing the proof.

Relevant quote I just found in the paper "Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents":

The primary measure of an agent’s performance is the score achieved during an episode, namely the undiscounted sum of rewards for that episode. While this performance measure is quite natural, it is important to realize that score, in and of itself, is not necessarily an indicator of AI progress. In some games, agents can maximize their score by “getting stuck” in a loop of “small” rewards, ignoring what human players would consider to be the game’s main goal. Nevertheless, score is currently the most common measure of agent performance so we focus on it here.

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