What you need to know about cryptoamnesia and design developed for applications
Basic concepts “cryptoeconomy”: If in 2017 you in contact with the world of cryptocurrencies, you probably met the term “cryptoamnesia”. If not, then perhaps you can be forgiven for having missed it among the more fascinating linguistic inventions in the cryptocurrency space. The post nick Tomaino and this video Vitalik Buterin can fill you in on the topic.
Usually say that the mechanism “implements” the function of social selection, if, at equilibrium, the compliance types and results what is the function of social choice (why mechanism design is sometimes called the “theory of implementation”). May be required to be implemented with dominant strategies (when this is true for the agent regardless of the strategies of other agents) or just implementation along with equilibrium Bayes – Nash (when neither player has a profitable deviation on the basis of their beliefs about the types and strategies of other players). The first option is obviously much more powerful (and therefore more limiting) assumption.
The principle of the disclosure
One of the fundamental results of mechanism design is the Principle of Disclosure. In the most General terms, it States that any social choice function that can be implemented with an arbitrary mechanism can also be implemented as a truthful mechanism with direct disclosure of information with the same equilibrium outcome. The mechanism of direct information disclosure is a mechanism where agents simply report to the mechanism their types, which leads to a decision and many transfers. The mechanism of direct disclosure of information is considered truthful if the truthful message of the preferences is a dominant strategy (although, in General, may require that it simply was true at equilibrium Bayes – Nash). Such mechanisms are called truthful, incentive compatible or non-manipulable. The principle of disclosure is particularly impressive effect. In short, when you can prove the validity of something for these engines, it proves its validity for all mechanisms! To understand why this is so, imagine a random untruthful mechanism with a front end that takes your preferences and strategically interacts with the mechanism to maximize your reward (as Trustee). Then you won’t want to falsely inform the interface to their preferences, otherwise you will get suboptimal reward. In fact, you don’t need to lie, because the mechanism does it for you! The observation that it is possible without compromising the generalization to focus only on truthful mechanisms with direct information disclosure is the key result, which makes the design of efficient mechanisms. Otherwise, you would have to prove the validity of theorems for large sets of indirect or untruthful mechanisms that would make this theme almost useless. Design mechanisms as constrained optimization
So, now that we have defined the basic concepts, to achieve what kind of results you can use mechanism design? What is a “good” mechanism, and how to make sure that we choose his name? We can consider this as an optimization problem where you try to maximize an objective function (such as your income), subject to certain limitations. It makes sense to present the most common limitations that you may encounter.