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Semi on-topic: pseudorandomness is an interesting idea that has interesting applications in real life. Maria Konnikova [1] mentions that poker players, even wh
by wenc 6y ago
Semi on-topic: pseudorandomness is an interesting idea that has interesting applications in real life.
Maria Konnikova [1] mentions that poker players, even when they have an on-average winning strategy, randomize their play using the second hand on their watches. For instance, they might execute their play 3 times every 4 plays, depending what their watches tell them.
For me the deeper implication is that in an environment with stochasticity (the real world is a mix between determinism and randomness), executing the same deterministic strategy all the time is likely not going to guard you against the random events that are harmful. Randomization provides a sort of protection by diversifying your strategies.
[1] in an interview with Sean Carroll on the Mindscape podcast
- kd5bjo 6y agoIn game theory, the optimal strategy is often a stochastic one. In those games, if you play deterministically there’s always a way for your opponent to gain an advantage; playing randomly from a particular distribution is strictly better for you. cf. https://en.wikipedia.org/wiki/Strategy_(game_theory)#Mixed_strategy https://en.wikipedia.org/wiki/Strategy_(game_theory)#Mixed_s...
- rmrfstar 6y ago+1 A good example of this is rock-paper-scissors. Imagine playing against someone with a non-random strategy.
- voxelghost 6y agoGood ol' rock always wins.
- wenc 6y agoI wonder if an example of randomization might be: put 80% of your apps in AWS, but randomly deploy the remaining 10% in Azure and 10% in GCP just so that your team has expertise in the latter two.
- skoocda 6y agoThis may also be an example of simply tripling your effort, while maintaining about 80% uptime.