You and I play the following game: You write two distinct, real numbers on two different sheets of papers (in a way such that I cannot read the numbers). Then I flip one of these sheets, read the number and guess whether the other number is higher or lower. If I guess right, I win, else you win.
There is one caveat: Before you write down your numbers, I will tell you my guessing strategy (a randomized algorithm, I have access to as much truly random data as I want).
Let's say the loser gives the winner 100\$ and my task is to make as much money as possible. There is a strategy with a winning percentage of more than 50%:
I choose a normally distributed random variable $X$. I choose one of the sheets uniformly at random. Let $A$ denote the number behind this sheet. If $X > A$, I say “$B>A$”, else I say “A>B”.
If $X$ is between $A$ and $B$ I win, else I have a winning percentage of $50\%$. As $P(X \in (A, B)) > 0$ my total winning percentage is larger than 50%. (This works with any random real variable having positive probability on all intervals.)
Problem: That strategy does not suffice to make a lot of money, given $\newcommand{\eps}{\varepsilon}\eps > 0$ you can choose your numbers in a way such that my winning percentage is smaller than $0.5 + \eps$. Even if we play the game 1000 times, you can choose your numbers such that my expected win is less than a cent.
That is nearly a fair game – how do I make substantially more money? Are there $\eps \gt 0$ and a strategy with a winning percentage of at least $0.5 + \eps$? I have to tell you my strategy before you choose your numbers.
Or is there no such strategy?
We are in a similar situation as in the following links.
(And in many others. There is not too much to say about why the chance to win is > 1/2, but as i started a wrong answer, now i rather correct it instead of deleting it. Very probably i would have not even started an answer form my today position of understanding.)
"My" strategy of play was to choose independently a random variable $Y$ with values in $\{S,T\}$ for some real values $S,T$ with $S<T$, uniformly distributed, then get the probability of win depending on the mean $\mu=EX$ and variance $\sigma^2$ of $X$.
Let $\bar Y = (S+T-Y)$. (So $\bar Y$ is $S$ if and only if $Y$ is $T$.)
Then we have a two-levels experiment, the first level being the choice of the sheet.
Then we have to compute the win probability $W$ with the described strategy $$ \begin{aligned} W =& \frac 12\Big( \ P( X>Y\text{ and }\bar Y>Y )+ P( X<Y\text{ and }\bar Y<Y )\ \Big)\\&\qquad\text{[ Sheet A is $Y$ ]} \\ +& \frac 12\Big( \ P( X>\bar Y\text{ and }Y>\bar Y )+ P( X<\bar Y\text{ and }Y<\bar Y )\ \Big)\\&\qquad\text{[ Sheet A is $\bar Y$ ]} \\[4mm] =& \frac 12\Big( \ P( X>Y\text{ and }Y=S )+ P( X<Y\text{ and }Y=T )\ \Big) \\ +& \frac 12\Big( \ P( X>\bar Y\text{ and }Y=T )+ P( X<\bar Y\text{ and }Y=S )\ \Big) \\[4mm] =& \frac 12\Big( \ P( X>S\text{ and }Y=S )+ P( X<T\text{ and }Y=T )\ \Big) \\ +& \frac 12\Big( \ P( X>S\text{ and }Y=T )+ P( X<T\text{ and }Y=S )\ \Big) \\[4mm] =& \frac 12\Big( \ P( X>S)+ P( X<T)\ \Big) \\ =& \frac 12+\frac 12 P(S\le X\le T)\ . \end{aligned} $$ Same as in the question.
There is nothing new above, only that i was trying to explain the things for myself in a very special case. Now the question is if there is a strategy that works with a better probability for you, based on the only information of the number of the number in one randomly chosen sheet, and i suppose, we still proceed in the following order:
Now to the question. Fix some $\epsilon >0$. We have an infinite family $(k(s))_{s\in\Bbb R}$ of numbers in $[0,1]$. Then we can find two members in the family, $k(S)$ and $k(T)$, so that $$ |k(S)-k(T)|<\frac {\epsilon}{2018}\ . $$ If i have the information in $(k(s))_s$, then i am choosing them in this way, and the probability that you win is smaller than $\frac 12+\epsilon$ with an argument similar to the above for a gaussian $X$ implementing the decision to keep the visible sheet.
Even if i do not have the information, there is a chance that i am randomly choosing two numbers $S,T$ with $|k(S)-k(T)|<\epsilon/2018$ with positive probability, so that you cannot "do better than $\frac 12+\epsilon$".