Monte Carlo Sims - Please check my algorithm - c++

Question

Basically, the problem simulates the following:
There is an urn with 50 green balls and 50 red balls.
I am allowed to pick balls from the urn, without replacement, with the following rules: For every red ball picked, I lose a dollar, for every green ball picked, I gain a dollar.
I can stop picking whenever I want. Worst case scenario is I pick all 100, and net 0.
The question is to come up with an optimal stopping strategy, and create a program to compute the expected value of the strategy.
My strategy is to continue picking balls, while the expected value of picking another ball is positive.
That is, the stopping rule is DYNAMIC.
In Latex, here's the recursive formula in an image:
http://i.stack.imgur.com/fnzYk.jpg
#include <stdio.h>
#include <math.h>
#include <stdlib.h>
double ExpectedValue(double, double);
double max(double, double);
main() {
double g = 50;
double r = 50;
double EV = ExpectedValue(g, r);
printf ("%f\n\n", EV);
system("PAUSE");
}
double ExpectedValue(double g, double r){
double p = (g / (g + r));
double q = 1 - p;
if (g == 0)
return r;
if (r == 0)
return 0;
double E_gr = max ((p * ExpectedValue (g - 1, r)) + (q * ExpectedValue (g, r - 1)), (r - g));
return E_gr;
}
double max(double a, double b){
if (a > b)
return a;
else return b;
}
I let it run for 30 minutes, and it was still working.
For small values of g and r, a solution is computed very quickly. What am I doing wrong?
Any help is much appreciated!

Answer 1

Your algorithm is fine, but you are wasting information. For a certain pair (g, r) you calculate it's ExpectedValue and then you throw that information away. Often with recursion algorithms remembering previously calculated values can speed it up a LOT.
The following code runs in the blink of an eye. For example for g = r = 5000 it calculates 36.900218 in 1 sec. It remembers previous calculations of ExpectedValue(g, r) to prevent unnecessary recursion and recalculation.
#include <stdio.h>
#include <stdlib.h>
double ExpectedValue(int g, int r, double ***expectedvalues);
inline double max(double, double);
int main(int argc, char *argv[]) {
int g = 50;
int r = 50;
int i, j;
double **expectedvalues = malloc(sizeof(double*) * (g+1));
// initialise
for (i = 0; i < (g+1); i++) {
expectedvalues[i] = malloc(sizeof(double) * (r+1));
for (j = 0; j < (r+1); j++) {
expectedvalues[i][j] = -1.0;
}
}
double EV = ExpectedValue(g, r, &expectedvalues);
printf("%f\n\n", EV);
// free memory
for (i = 0; i < (g+1); i++) free(expectedvalues[i]);
free(expectedvalues);
return 0;
}
double ExpectedValue(int g, int r, double ***expectedvalues) {
if (g == 0) return r;
if (r == 0) return 0;
// did we calculate this before? If yes, then return that value
if ((*expectedvalues)[g][r] != -1.0) return (*expectedvalues)[g][r];
double p = (double) g / (g + r);
double E_gr = max(p * ExpectedValue(g-1, r, expectedvalues) + (1.0-p) * ExpectedValue(g, r-1, expectedvalues), (double) (r-g));
// store value for later lookup
(*expectedvalues)[g][r] = E_gr;
return E_gr;
}
double max(double a, double b) {
if (a > b) return a;
else return b;
}

Answer 2

Roughly speaking, adding one ball to the urn doubles the number of calls you will have to make to ExpectedValue (let's not quibble about boundary conditions). This is called O(en), and it can bring the most powerful computer on Earth to its knees.
The problem is that you are calculating the same values over and over again. Keep a table of ExpectedValue(r,g) and fill it in as you go, so that you never have to calculate the same value more than once. Then you'll be working in O(n2), which is heck of a lot faster.

Answer 3

In my opinion, correct, but rather straightforward solution.
Here's what you can do:
Eliminate recursion!
Eliminate recalulations of ExpectedValue
Parallelize your code
Read this [lecture notes]. It definitely will be useful
I can provide some code samples, but it'd not be fair.