Steve,
Nice to hear from you once again! I appreciated your posts a few months
back, and I'm glad the vpFREE admin posted the information at
http://members.cox.net/vpfree/FAQ_S.htm but I'm still trying to fully
understand it. I have a few questions:
1. How do you come up with values to use in the paytable for a given
goal?
That is the hardest part of all -- finding a mathematical relationship
between the number of units in the payoff and the real "value" of that
payoff in terms of the goal.
Your 9/6 min-cost-royal paytable uses a value of 4879.97 for the royal,
which makes the game's ER 100.0% - that I can understand (I think). But
what about the others, like min-risk (which seems like the most important
to understand)? You refer to a formula for stretching the values; what is
the formula you used?
For min-risk, the formula is:
VP = (1 - R^N) / (1 - R)
where VP is the "Virtual Payoff", R is the risk parameter for the strategy
being used (same as RoR if the game if favorable to the player)
and N is the actual payoff value.
The min-risk strategy seeks to maximize the probability of playing
forever without going broke. When starting with a single unit, R is
the probability of ruin, so (1 - R) is the probability of success. Now,
if you play that one unit and hit a payoff of N units, then you've traded
your initial one-unit bankroll for an N-unit bankroll. The probability of
eventually losing the entire N unit bankroll is R^N, so the probability
of going on to play forever is (1 - R^N). So, (1 - R^N) is the probability
of success for playing an N unit bankroll.
You could just use the (1 - R^N) values for the virtual payoffs, because
they are the raw probabilities of success that go with each payoff N.
In fact, you could take these raw probabilities and scale them all up
by any factor you want, as long as all of them are scaled by the same
factor, and you could use those number to represent the "value" of
the payoffs. Scaling by dividing them all by (1 - R) does two things
that are useful. First, it gives numbers for virtual payoffs that are "close"
to the actual payoff value, and this can give you a feel for how the
goal stretches the values compared to computing EV. The other thing
this does is express the virtual payoffs as a multiple of the chance for
success that you get from a bankroll of one unit. So, if a payoff of 50
units gives a virtual payoff of 49.6 units, then this means that a payoff
of 50 increases your probability of playing forever by a factor of 49.6
compared to you chance of success for a single unit bankroll. Similarly,
a royal payoff of 1300 units might give a virtual payoff of 1009 units,
which would mean that turning one unit into 1300 units increases your
probability of playing forever by a factor of 1009. So, 1009 is the "value"
of that payoff in terms of the probability of reaching your goal of
playing forever.
These raw success probabilities satisfy the equation:
(1 - R) = p(1)*(1 - R) + p(2)*(1 - R^2) + ... + p(25)*(1 - R^25)
+ p(50)*(1 - R^50) + p(1300)*(1 - R^1300)
The real meaning of the above equation is this: The overall probability
of success for a 1 unit bankroll is (1 - R) and that value (on the left side
of the equation) is equal to the sum of all the possibilities that can
result from playing the game. For each possible payoff N, p(N) is the
probability of receiving that payoff, and (1 - R^N) is the probability
that those N units will be enough to allow you to keep playing forever.
Now if we divide both sides of the equation by (1 - R), we get an equation
and has the number one on the left, and on the right is a formula that
multiplies the p(N) values by the "virtual payoffs" [(1 - R^N) / (1 - R)].
This new equation means "the average value of the virtual payoffs is one".
In other words, when the game is viewed from the perspective of these
virtual payoffs, it appears that we are playing a breakeven game.
I understand the computations and strategy generation
once you have a paytable, but arriving at the adjusted values is somewhat
of a mystery to me. And you could say I'm math-inclined, so I must not be
the only one! The descriptions of the process on the above page don't quite
get me there. You say it's complicated, so maybe I'm opening a can of worms
here. I also get max-royal (we've discussed that here in relation to
tournaments). You set everything but the royal to zero (and the value for
the royal payoff is irrelevant, it can be 1 or 4000 or a million - you'll
still get the same resulting strategy). So perhaps you can tell us how you
arrived at the min-risk paytable, that should help.
I hope the description about helped rather than just making it more confusing,
but it was kind of rushed (I'm late for work) so please ask more questions if
it doesn't make sense.
2. Can we obtain the software you used for this analysis?
You apparently have software of your own that allows fractional paytables
that you use for these purposes. Are you willing to give it away or sell
it? I'm sure some others here might be interested in it. I have begun
developing such a beast, but it's not finished.
My program only works for games with no wild cards, and it is an unfinished
work, so I'd rather no distribute it.
It's an interesting universe you've explored, where max-EV is not always
the goal but just one possible goal. I'm hoping to understand it better.
Yes it is, and I'm always looking for new types of goals to evaluate.
Someone here recently asked about getting the best shot at reaching
a fixed coin-in requirement, as their definition of "success". This leads
to a complex strategy that has some interesting characteristics, so I'm
trying to find some time to explore that goal in more detail.
···
On Thursday 20 July 2006 2:04 am, John Douglass wrote: