In terms of expected value this is the same as making the £10 vs £20 bet a bunch of times, but it has a much higher variance: the chance of getting an extreme outcome has gone up a lot.
Sometimes failing at things makes it harder to try in future even if you expect things to go well, and sometimes people are so afraid that they give up on trying, but you can break out of this by making small, careful bets with your energy.
Researchers and educators have long wrestled with the question of how best to teach their clients be they humans, non-human animals or machines. Here, we examine the role of a single variable, the difficulty of training, on the rate of learning. In many situations we find that there is a sweet spot in which training is neither too easy nor too hard, and where learning progresses most quickly.
...the optimal error rate for training is around 15.87% or, conversely, that the optimal training accuracy is about 85%
One might benefit from modulating their learning so that their failure rate falls in the above range (assuming the findings are accurate).
EV is not measured in money but in utilons.
reminds me of this article
One might benefit from modulating their learning so that their failure rate falls in the above range (assuming the findings are accurate).
Sounds like https://www.lesswrong.com/tag/kelly-criterion might be useful reading!