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Update Then Forget

5y
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How to Be Oversurprised

5y
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How to Disentangle the Past and the Future

5y
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Point-Based Value Iteration

6y
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Internal Availability

6y
2 min read
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The Bayesian Agent

6y
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Reinforcement, Preference and Utility

6y
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Reinforcement Learning: A Non-Standard Introduction (Part 2)

6y
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Reinforcement Learning: A Non-Standard Introduction (Part 1)

6y
2 min read
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19

The Perception-Action Cycle

6y
1 min read
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12

Recent Comments

It seems that your research is coming around to some concepts that are at the basis of mine. Namely, that noise in an optimization process is a constraint on the process, and that the resulting constrained optimization process avoids the nasty properties you describe.

Feel free to contact me if you...(read more)

This is not unlike Neyman-Pearson theory. Surely this will run into the same trouble with more than 2 possible actions.

Our research group and collaborators, foremost Daniel Polani, have been studying this for many years now. Polani calls an essentially identical concept [empowerment](http://homepages.stca.herts.ac.uk/~comqdp1/publications/files/cec2005_klyubin_polani_nehaniv.pdf). These guys are welcome to the party...(read more)

You have a good and correct point, but it has nothing to do with your question.

> a machine can never halt after achieving its goal because it cannot know with full certainty whether it has achieved its goal

This is a misunderstanding of how such a machine might work.

To verify that it completed ...(read more)

> The "world state" of ASH is in fact an "information state" of p("heads")>SOME_THRESHOLD

Actually, I meant p("heads") = 0.999 or something.

> (C), if I'm following you, maps roughly to the English phrase "I know for absolutely certain that the coin is almost surely heads".

No, I meant: "I know f...(read more)

I probably need to write a top-level post to explain this adequately, but in a nutshell:

I've tossed a coin. Now we can say that the world is in one of two states: "heads" and "tails". This view is consistent with any information state. The information state (A) of maximal ignorance is a uniform di...(read more)

To clarify further: likelihood is a relative quantity, like speed - it only has meaning relative to a specific frame of reference.

If you're judging my calibration, the proper frame of reference is what I knew at the time of prediction. I didn't know what the result of the fencing match would be, b...(read more)

This is perhaps not the best description of actualism, but I see your point. Actualists would disagree with this part of my comment:

> If I believed that "you will win" (no probability qualifier), then in the many universes where you didn't I'm in Bayes Hell.

on the grounds that those other univer...(read more)

we've already seen [...] or [...] in advance

Does this answer your question?

Predictions are justified not by becoming a reality, but by the likelihood of their becoming a reality [1]. When this likelihood is hard to estimate, we can take their becoming a reality as weak evidence that the likelihood is high. But in the end, after counting all the evidence, it's really only t...(read more)