Vitalik Buterin the co-found of Ethereum gave a talk at Blockchain Labs about cryptoeconomics, which is a really fascinating concept. Crytpoeconomics is the combination of cryptography — the ability to hide information in plan sight — and economics — specifically game theory’s Iterated Prisoner’s Dilemma. Combined it creates for an ecosystem with self imposing rules within the same ecosystem that keep the ecosystem functioning properly (tongue twister). It’s worth listening to his talk on the subject.
Figure 1
Before defining an Iterated Prisoner’s Dilemma, it’s first important to define a Prisoner’s Dilemma. It’s the concept of cooperation vs. defection. In the classical example, two persons suspected of a crime are taken into two different rooms, the cops say to both of you: “We believe you are innocent and want you to rat out your friend.” What do you do? In Figure 1, these players are awarded different payouts for different choices. Each choice is represented by a number of months each players will get in jail if they chose to confess vs. don’t confess that the other person committed the crime. The payouts can be read as (Player 1, Player 2). Logically, each player prefers to get no time in jail. The optimal strategy for Player 1 then is to confess that the other player committed the crime hoping the other player didn’t accuse them. This would result in no time in jail — the same goes for Player 2. However, if they both confess that the other person did the crime, they’ll both end up with 6 months behind bars, and if the both don’t confess they’ll receive only 1 month in jail. In a static Prisoner’s Dilemma game, the desired strategy for both participants is to confess and hope the other person didn’t. Even if you’re confident the other person will confess that you did the crime, the prospect of spending 6 month in jail instead of 10 months is still better, so your Nash Equilibrium (the optimal strategy where no other strategy prevails) is to confess.
This changes with the Iterated Prisoner’s Dilemma. This strategy was developed by Robert Axelrod, which follows a tit-for-tat strategy. It assumes that everyone is operating on their own self-interest, and each individual takes into account the future as an aspect of their self-interest. Instead of choosing a position that could hurt them in the long run each player will decide to make decisions in an altruistic way, knowing that if anyone deviates from the strategy of altruism that they will be punished next round by the other player. This continues until both players stop trying to punish one another. This theory was further refined by incorporating Pavlov into the Prisoner’s Dilemma. This expands on the tit-for-tat theory by having Pavlov “learn by conditioned response, through rewards and punishments, to cooperate or defect.” A Pavlov player is trained and operates on probabilities trying to find the optimal payout for the long run. It will still act in an almost altruistic way, only if the competing player cannot retaliate since this a highly rewardable strategy in our example. It will quickly find out what strategy is best for the long run and, if retaliation does exists, move back to an altruistic strategy. This does two things, it solves for drawn-out tit-for-tat battles that can go on indefinitely which only hurt the ecosystem, and exploits suckers that don’t understand the system which can depress the value of the ecosystem (in certain games).
Blockchains use these strategies in game theory to ensure cooperation and consensus in the ecosystem for each block on the chain. The cryptography is not the new aspect of blochchain technology, it’s the incorporation of economics that changes how information is secured. Pretty neat!