Governance in NeuroChain is the democratic process, which administers Bot interactions. These statutes allow reaching a consensus in the network and trigger action flows. Proof of Involvement and Integrity and proof of workflow are self-consistent consensus algorithms based on three independent parameters reflecting the involvement, value holding and integrity of each Bot. The consensus architecture induces a dose of chance, which makes the consensus not fully predictable by the algorithms. In other words, predictions are from a probabilistic stand point, uncertain.
The feedback to each Bot due to Machine Learning algorithms will ensure, at posteriori, the integrity of the Bots. This retro action of the network on the Bots and therefore on the consensus will provoke quarantine or isolation of dishonest Bots.
The governance consensus is also flexible because amendments are possible due to the different adjustment parameters.
The following table illustrates the dynamic parameters and their impact on the decision process.
Flexibility of the protocol
The different parameters listed above, reflect the extreme flexibility of the protocol while keeping all the guarantees of security, vivacity and correctness (each parameter counterbalances the others). The election process based on the constitution of the assemblies ensures a high level of randomness in the selection of the leaders but also a high performance in the execution of the protocol since the assembly is elected for a dynamic number of validations of blocks evolving according to evolution of the network entropy and integrity. The evolution of the network during a mandate will allow a certain renewal in the assembly.