Your cake example reminds me of a basic, yet interesting, optimisation problem.
How do you get 2 children to share fairly a cake?
As we know, people will look at the tiniest difference to get the larger share.
The solution is that you let one child cut the cake into two parts, then let the other child have first pick of their slice.
The solution is sooo simple... ;-)
However, it is (still?) a mystery to me how we can break this metaphor down to our core problem with many, many children. And the coding of it even more so! But in the end this is fortunately the task of competent mathematicians and computer scientists.
Exactly! The multi-person cake-cutting problem is, however, not so simple.
https://en.wikipedia.org/wiki/Fair_cake-cutting
It is one of many algos I am looking at - thinking takes time tho ;-)
What the h...! Chapeau if you manage to tailor this insane challenge as an algorithm to our concerns!
Maybe step by step, trial and error? Rome was not created in one day... ;-)
Happy Easter,
warm regards,
Chriddi
That's kinda my job! :-)
Thing is, many of these algos assume an agent-ignorance, a lack of total info, so that agents (sometimes human) act with incomplete knowledge, eg. the Prisoner's Dilemma is only a dilemma because the two people cannot communicate, so each has partial knowledge.
But on a blockchain, one can extract a lot of data so that, in theory, everybody acts from a POV of full-knowledge, not partial. This means decisions can be taken with global consequences in mind. This makes it easier to form allegiances on-chain that can break some of the purity of the algorithms.
I've said this many times, and perhaps takes some time to really sink in to the public: that after writing an algorithm, when you try to optimise its effects, it can end up doing something very different to the original intention.
Just as the 2-person cake sharing is easy, but many-people is hard - not just the process but also potential collusion among cake-lovers.