>>480 つづき

Nevertheless, we choose this presentation because we find it the most interesting, as well as pedagogically useful.
For instance, “predicting the present” is a very natural way to think of the problem of guessing the value of f (t) based on f |(?∞, t).

2. THE μ-STRATEGY.
(詳細は略すので、原文ご参照。ここに引用するには、数学記号が複雑過ぎるので。)

P92
3. PREDICTING THE PRESENT.
(詳細は略すので、原文ご参照。ここに引用するには、数学記号が複雑過ぎるので。)

Corollary 3.4. If T = R and ∇ is <, then W0 is countable, has measure 0, and is nowhere dense.

What Corollary 3.4 tells us is that, if we model the universe as a function from the real numbers into some set of states, then the μ-strategy will correctly predict the present from the past on a set of full measure.
(In the following section, we show that, on a set of full measure, it correctly predicts some of the future as well.)
Note that these results concerning T = R are also valid when T is any interval of reals.
One needs to be cautious about interpreting this as meaning that the μ-strategy is correct with probability 1.
For a fixed true scenario, if one randomly selects an instant t in the interval [0,1] (or in R, under a suitable probability distribution), then
Corollary 3.4 does tell us that the μ-strategy will be correct at t with probability 1.
However, if one fixes the instant t, and randomly selects a true scenario, then the probability that the μ-strategy is correct at t under that scenario might be 0 or might not even exist, depending on how one defines the notion of a random scenario.

P95
W = {t ∈ R | the μ-strategy does not guess well at t }.
Theorem 5.1. The set W is countable, has measure 0, and is nowhere dense.

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