How does NGK apply control theory to the crypto industry?

The crypto economy system and the control system of NGK have a common phenomenon. There is a set of parameters set by humans, which encode the trade-off decisions in the system. Under the crypto economy system, we regard the parameters subject to human supervision as the governance aspect.

It is important for NGK to clarify the governance aspect, and where possible, it is important that the effect of adjusting this parameter is relatively straightforward. In general, the concept of governance is used as a general concept, assuming that humans will have the expertise, procedures, and coordination to agree on future changes to these parameters.

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In practice, NGK aims to maintain a small governance area to reduce the frequency and complexity of governance actions. In addition, system engineering based on the early model can determine the initial parameters to develop the rollout plans and/or minimize the scale of future changes.

From stablecoins anchored to the US dollar to the recent popular algorithmic stablecoins, can “stable” assets create new gameplay? The NGK continues to monitor the real-time data and integrates with the system model, which will reveal whether it is worth including the integrated control item Ki and its leaked “anti-saturation” mechanism. This will increase the complexity of the system, but it can also ensure the long-term sustainability, thereby minimizing the governance during the life cycle of the RAI system.

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Trying to minimize governance by ignoring the governance is like getting on a self-driving car without instructing the destination to the car.

In practice, the minimization of governance requires a clearly defined governance aspect, and then a clear procedure about who, when, and how to change the parameters. Successful governance minimization means making fewer, smaller, and clearer changes, and reducing the business costs.

It is rare that the parameters are completely uncoupled. More often, the appropriate values ​​are related to each other, such as the Kp, Ki, and α (leakage integrator) we have seen. The NGK models play an important role in monitoring the health of the system because they can suppress the governance actions, which actually put the system at risk and in turn helping to determine when actions are needed. There are sufficient warnings to execute planning, testing, and implement effective interventions.

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Given that NGK has a full-featured model of RAI and mainnet, it will next expand the scale of the existing model and integrate it with real-time data to provide information for continuous monitoring. After that, we must make a decision to learn from shocks and events to improve our understanding of the complex new dynamics around us.

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