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From: Jesse Mazer <lasermazer.domain.name.hidden>

Date: Tue, 05 Oct 2004 00:28:50 -0400

Norman Samish:

*>The "Flip-Flop" game described by Stathis Papaioannou strikes me as a
*

*>version of the old Two-Envelope Paradox.
*

*>
*

*>Assume an eccentric millionaire offers you your choice of either of two
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*>sealed envelopes, A or B, both containing money. One envelope contains
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*>twice as much as the other. After you choose an envelope you will have the
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*>option of trading it for the other envelope.
*

*>
*

*>Suppose you pick envelope A. You open it and see that it contains $100.
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*>Now you have to decide if you will keep the $100, or will you trade it for
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*>whatever is in envelope B?
*

*>
*

*>You might reason as follows: since one envelope has twice what the other
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*>one
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*>has, envelope B either has 200 dollars or 50 dollars, with equal
*

*>probability. If you switch, you stand to either win $100 or to lose $50.
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*>Since you stand to win more than you stand to lose, you should switch.
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*>
*

*>But just before you tell the eccentric millionaire that you would like to
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*>switch, another thought might occur to you. If you had picked envelope B,
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*>you would have come to exactly the same conclusion. So if the above
*

*>argument is valid, you should switch no matter which envelope you choose.
*

*>
*

*>Therefore the argument for always switching is NOT valid - but I am unable,
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*>at the moment, to tell you why!
*

*>
*

Basically, I think the resolution of this paradox is that it's impossible to

pick a number randomly from 0 to infinity in such a way that every number is

equally likely to come up. Such an infinite flat probability distribution

would lead to paradoxical conclusions--for example, if you picked two

positive integers randomly from a flat probability distribution, and then

looked at the first integer, then there would be a 100% chance the second

integer would be larger, since there are only a finite number of integers

smaller than or equal to the first one and an infinite number that are

larger.

For any logically possible probability distribution the millionaire uses, it

will be true that depending on what amount of money you find in the first

envelope, there won't always be an equal chance of finding double the amount

or half the amount in the other envelope. For example, if the millionaire

simply picks a random amount from 0 to one million to put in the first

envelope, and then flips a coin to decide whether to put half or double that

in the other envelope, then if the first envelope contains more than one

million there is a 100% chance the other envelope contains less than that.

For a more detailed discussion of the two-envelope paradox, see this page:

http://jamaica.u.arizona.edu/~chalmers/papers/envelope.html

I don't think the solution to this paradox has any relation to the solution

to the flip-flop game, though. In the case of the flip-flop game, it may

help to assume that the players are all robots, and that each player can

assume that whatever decision it makes about whether to switch or not, there

is a 100% chance that all the other players will follow the same line of

reasoning and come to an identical decision. In this case, since the money

is awarded to the minority flip, it's clear that it's better to switch,

since if everyone switches more of them will win. This problem actually

reminds me more of Newcomb's paradox, described at

http://slate.msn.com/?id=2061419 , because it depends on whether you assume

your choice is absolutely independent of choices made by other minds or if

you should act as though the choice you make can "cause" another mind to

make a certain choice even if there is no actual interaction between you.

Jesse

Received on Tue Oct 05 2004 - 00:29:57 PDT

Date: Tue, 05 Oct 2004 00:28:50 -0400

Norman Samish:

Basically, I think the resolution of this paradox is that it's impossible to

pick a number randomly from 0 to infinity in such a way that every number is

equally likely to come up. Such an infinite flat probability distribution

would lead to paradoxical conclusions--for example, if you picked two

positive integers randomly from a flat probability distribution, and then

looked at the first integer, then there would be a 100% chance the second

integer would be larger, since there are only a finite number of integers

smaller than or equal to the first one and an infinite number that are

larger.

For any logically possible probability distribution the millionaire uses, it

will be true that depending on what amount of money you find in the first

envelope, there won't always be an equal chance of finding double the amount

or half the amount in the other envelope. For example, if the millionaire

simply picks a random amount from 0 to one million to put in the first

envelope, and then flips a coin to decide whether to put half or double that

in the other envelope, then if the first envelope contains more than one

million there is a 100% chance the other envelope contains less than that.

For a more detailed discussion of the two-envelope paradox, see this page:

http://jamaica.u.arizona.edu/~chalmers/papers/envelope.html

I don't think the solution to this paradox has any relation to the solution

to the flip-flop game, though. In the case of the flip-flop game, it may

help to assume that the players are all robots, and that each player can

assume that whatever decision it makes about whether to switch or not, there

is a 100% chance that all the other players will follow the same line of

reasoning and come to an identical decision. In this case, since the money

is awarded to the minority flip, it's clear that it's better to switch,

since if everyone switches more of them will win. This problem actually

reminds me more of Newcomb's paradox, described at

http://slate.msn.com/?id=2061419 , because it depends on whether you assume

your choice is absolutely independent of choices made by other minds or if

you should act as though the choice you make can "cause" another mind to

make a certain choice even if there is no actual interaction between you.

Jesse

Received on Tue Oct 05 2004 - 00:29:57 PDT

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