  Using game and probability theories, I study the French popular game 421, a
perfect information stochastic stage game. The problem is to find strategies
maximizing the probability of some expected utility. I only solve a player's
round against providence, a problem of fate stochastic management: beyond the
backward induction solution, bounded complexity motivates heuristic policies.
For a unique goal utility, a simple optimal policy, ratchet, is obtained. Its
result probabilities are compiled and used, for arbitrary utilities, as the
logic of goal identification policies. Various policies appear, close to human
behavior, and are exactly evaluated by solving the Kolmogorov equation.
