When I was reading the documentation of Fabric Foundation I came across the Hybrid Graph Value model. It really got me thinking.
This is not something you usually see in blockchain systems.
The Hybrid Graph Model does not reward people who participate based on how much money they make or just based on how much they do.
The Hybrid Graph Model rewards people based on both of these things. It changes the importance of each one as the network gets older.
At the beginning what people do is more important because the system is still growing.
On the Hybrid Graph Model cares more about the real work that people do and the money they make.
I think this is a way to do things because it makes sure that people who help out at the beginning are not ignored just because the system is not making a lot of money yet.
What I really like about the Hybrid Graph Model is that it stops people from cheating the system.
If someone tries to cheat by making transactions the Hybrid Graph Model does not give them any credit for it.
The Hybrid Graph Model only rewards people who really participate and do work.
It does not reward people who just try to trick the system.
To me the Hybrid Graph Model is trying to do something
The Hybrid Graph Model is not just giving out tokens it is trying to figure out who is really contributing to the system.
This is a problem to solve because the system is made up of a lot of different parts, including robots and users.
The Hybrid Graph Model tries to solve this problem by combining what people do how money they make and how they are connected to each other.
I think this is a way to try to solve the problem.
If we want robotics networks to work in the world we need to make sure that people have a good reason to participate.
The Hybrid Graph Model is trying to do this by making sure that people are rewarded for the work they do.
The Hybrid Graph Model. Adapts as the system grows which I think is exactly what it should do.
@Fabric Foundation #ROBO $ROBO
