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Pavitra comments on LW is to rationality as AIXI is to intelligence - Less Wrong
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I don't understand the question. Can you explain what was wrong with the answer I just gave?
The question is: please recommend a model of rationality that a human can actually use in the real world. It's not clear to me in practice how I would use, say, gzip to help make predictions.
Right, well, the link between forecasting and compression was gone over in this previously-supplied link. See also, the other introductory material on that site:
http://matchingpennies.com/machine_forecasting/
http://matchingpennies.com/introduction/
http://matchingpennies.com/sequence_prediction/
If you want to hear something similar from someone else, perhaps try:
http://www.mattmahoney.net/dc/rationale.html
I understand the theoretical connection. I want a real-world example of how this theoretical result could be applied.
An example of prediction using compression?
E.g. see Dasher. It uses prediction by partial matching.
I also found this thesis, 'Statistical Inference through Data Compression', using gzip of all things, quite interesting. (Some half-related background.)
That is indeed a correct answer to a reasonable interpretation of the question I asked. I thereby realize that I should have asked differently.
Where examples of rationality usage are given on LW, they tend to be of the straightforward decision-theoretic kind, such as solving the trolley problem; that is, rationality and studied and taught here is mostly about helping humans better make the kinds of decisions that tend to be made by humans.
Suppose I want to take an umbrella to work with me if and only if it will rain this afternoon. How might I go about deciding whether to take my umbrella? And, in particular, is running my own statistical analysis on the weather patterns in my local area over the past hundred years really a better choice than just turning on the weather channel?
Perhaps I am missing something, but the answer is obviously no. This follows from the usual humility and outside view arguments, and from more detailed inside view considerations like the following: the weather station has access to far more data than you over that time period, and has detailed recent data you do not, and can hire a weather statistics expert (or draw on such expertise) who will crush your predictions because they specialize in such problems.
The answer was intended to be obviously no. I wished to refute the idea that esoteric mathematical models like prediction-as-data-compression translated directly into useful advice for the real world outside of a few highly technical cases.