The idea here has stuck with me as one of the best nuggets of wisdom from the sequences. My current condensation of it is as follows:
If you let reality have the final word, you might not like the bottom line. If instead you keep deliberating until the balance of arguments supports your preferred conclusion, you’re almost guaranteed to be satisfied eventually!
If instead you keep deliberating until the balance of arguments supports your preferred conclusion, you’re almost guaranteed to be satisfied eventually!
Inspired by the above, I offer the pseudo code version...
loop {
if assess(args, weights) > 1 { // assess active arguments
break; // preferred conclusion is "proved"
} else {
arg = biased_sample(remaining_args); // without replacement
args.insert(arg);
optimize(args, weights); // mutates weights to maximize `assess(args, weights)`
}
}
… the code above implements “the balance of arguments” as a function parameterized with weights. This allows for using an optimization process to reach one’s desired conclusion more quickly :)
The idea here has stuck with me as one of the best nuggets of wisdom from the sequences. My current condensation of it is as follows:
If you let reality have the final word, you might not like the bottom line. If instead you keep deliberating until the balance of arguments supports your preferred conclusion, you’re almost guaranteed to be satisfied eventually!
Inspired by the above, I offer the pseudo code version...
… the code above implements “the balance of arguments” as a function parameterized with weights. This allows for using an optimization process to reach one’s desired conclusion more quickly :)