Cerrisian Blog

Bayesian decision theory basically states that you sum over all possible theories of events, and then multiply the probability of an event times the payoff to determine the optimal action.

The question is, what do you do when you don’t know what the probability of an event is? What do you know if you don’t know what the payoff is?

The answer is in Pascal’s wager, assuming you can determine whether the payoff is bounded or unbounded, (either negative or positive) you base your decision solely on the payoff and not on the probability.

This is of course a heuristic and can be abused by silly people, but it’s still a good general description.

If you are looking for high payoff events that you don’t know when they’ll occur, you have to maximize your serendipity. That’s what I’m trying to focus on more and more in my life, maximizing serendipity.