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This one is from "A Programming Approach to Computability" , by A.J. Kfoury, Robert Moll, & Michael Arbib (1982), on page 77.
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Are these guys kidding, or what?
In every previous instance that I have found in this book, they used \leq to represent "less than or equal to". Here, I guess maybe they are using it to signify "is a subset of". But even if that's the case, how do they conclude (in the second paragraph), that "if \sigma(y) is defined, it equals \mu(y)"?
I can't say that I like this stuff, but I'm determined to understand it if I can, so any suggestions will be appreciated.
How do they get all that out of \sigma \leq \mu ?3 Example Let \sigma:N \rightarrow N and \mu:N \rightarrow N be two computable functions such that \sigma \leq \mu. This means that whenever \sigma (y) is defined, so is \mu (y), and in this case we must have \sigma (y) = \mu (y). Thus \sigma is a subset of \mu when considered as a set of ordered pairs of natural numbers.
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Now define \psi_3 by the specification:
\psi_3(x,y) = \left \{ \begin{array} {cc} \mu(y), &\text{if} \;\phi_x(x)\downarrow \\<br /> \sigma (y), &otherwise \end{array}\right
At first glance, the second line asks us to return a value \sigma(y) based on the assumption that computation Px on x runs on forever. But on closer inspection, we realize that \sigma \leq \mu tells us that if \sigma(y) is defined it equals \mu(y). Thus we can compute \psi_3(x,y) as follows: Start the computations of \sigma(y) and of Px at the same time. If a result \sigma(y) is returned, halt--for then \sigma (y) = \mu (y) is the desired answer, no matter whether or not Px halts on x. But if Px halts on x before a result \sigma(y) is returned, stop computing \sigma(y) and start computing \mu(y). If and when this computation halts, the \mu(y) then returned is the desired answer.
Are these guys kidding, or what?
In every previous instance that I have found in this book, they used \leq to represent "less than or equal to". Here, I guess maybe they are using it to signify "is a subset of". But even if that's the case, how do they conclude (in the second paragraph), that "if \sigma(y) is defined, it equals \mu(y)"?
I can't say that I like this stuff, but I'm determined to understand it if I can, so any suggestions will be appreciated.