CFP-2208-16: Economical Simulation Framework to Predict Effects of Consensus Changes on the Ecosystem (30 000 DFI) #210
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kynkong91
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Look at the mess with dusd. We need simulation. $ defi-cli signmessage 8Vm9Xt1pB7vzkJdCaJihT4rKKMjmLkdUDC "cfp-2208-16-yes" |
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Overview
TL;DR
This proposal comprises the development and research of an economical simulation framework for the Defichain, which can be used to thoroughly test the effects of consensus changes (like the DFI Loan-Burn feature which resulted in unbacked DUSD) on the entire Defichain ecosystem. Since hundreds of thousands of users interact on the blockchain in complex ways, making it difficult to visualize or understand the interactions in every detail by merely thinking about it, this simulation framework can help to conduct empirical studies in a safe, artificial environment without having to "try out" new features on the live blockchain.
Background
Testing a new feature - for example a new way to pay off loans or a change in lending- or DEX fees - merely on the testnet alone is not enough. While this approach can ensure that the implementation is operating as intended, this does not give us an idea of what will happen on a macroscopic level (i.e. a top down view onto the entire Blockchain) when a large number of people start interacting with it. Agent-based simulation models are typically used to predict such effects; those models are "microscopic models" that simulate the simultaneous operations and interactions of multiple egoistic agents in an attempt to re-create and predict complex phenomena (such as the aforementioned DUSD depeg) on a "macroscopic level".
Typically, there are a number of different types of egoistic agents on the blockchain; however, they have all in common that they want to increase their yield. Examples may include the following, however, a thorough identification of key traits of these agents will be part of this project:
Moreover
The different agent models will probably be more complex than that, and we will identify the most prevalent specimen in the context of this research project.
Accuracy of Hypothetises
An economic simulation model as proposed here always is a simplified description of reality, designed to yield insights about economic behavior of large multi-agent systems inside a certain framework. While it does not fully resemble the reality, we aim to maximise the accuracy of the predictions so as to offering the core developers reasonable deductions for the real-world
A MVP Demonstration
As an MVP (or demonstration) we could take the data from the hardfork that introduced the DUSD payback via DFI burn and run various simulation to see the outcome of the DUSD price in the current market condition. Then we could test if we can find enough evidence in the data, that could have predicted the current outcome (DUSD discount). That will give us a good feel for the accuracy of the simulator's prediction capabilities.
Use of Funds
We are not asking much, its more like a symbolic value and it does not remotely reflect the amount of time we expect to invest. The funds will be spent as follows:
Kuegi: 10,000 DFI
Sandrich: 10,000 DFI
Daniel: 10,000 DFI
Code Deliverables
The entire code will be developed by us live on github and will be available for the community under the MIT license. During the development process we will be asking for feedback from the core developers, monitoring any newly suggested DFIPs and also provide a documentation for everyone to be able to quick start their way into the wonderful world of simulations.
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