Blockchain Economics: Merging Game Theory and Crypto-economics
Game theory has long been used in traditional systems to understand the actions of people in competitive situations, but applying these techniques to distributed systems in Web3 to analyze blockchain interactions is a whole new development. Here is a rundown of what this is about.
If you play chess regularly, you would know that for every move, there is a certain level of strategy behind it. In like manner, games of different genres have their own strategies and tactics to keep things interesting.
Game theory postulates that in any interactive game of interest, there are three major components:
- the players,
- their strategies, and
- the payoffs.
In these scenarios, the players are the parties who make the decisions, the strategy is the sum of all the decisions made by the parties (usually to win the game), and the payoffs are the resultant effects of all implemented strategies and the decisions made by the players.
Game theory was postulated in a bid to understand and map the correlation between these three major components.
Still centering the context around competitive games for instance, sociologists categorize games into two broad categories based on rationality. These categories are zero-sum games and non-zero-sum games.
Zero-sum and Non-zero-sum Games
In zero-sum games, there is an inverse relationship between winning and losing. In simpler terms, a player winning implies that the other players are losing. Board games are the best examples of such games. In game theory terms, the sum of player payoffs always adds up to the same value; i.e. if you lose, another player wins.
On the other hand, you are playing a non-zero-sum game if multiple players benefit from your actions. The effective payoffs to be distributed depend on the extent to which the players cooperate.
Game theory, in simple terms, studies strategies and tactics in a competitive context. It describes the behaviour of individual players and the actions that they take when faced with the choices available to them.
Game theory is concerned with the strategic interaction of rational decision-makers, who know their environment and the potential outcomes from decisions made in that environment, and then attempt to find a solution that will be most beneficial to them or optimize their payoff.
Now, what exactly is the game theory and how is it applicable in distributed systems as seen in Web3?
Game Theory Explained
Game theory is a mathematical and sociological theory of conflict and cooperation. It can be used to understand situations that are cross-sectional in terms of time dependence (i.e. events where one occurs as a result of the other) — such as auctions, lotteries, and negotiations.
Game theory (originally called metamathematics) as a branch of mathematical philosophy, studies decision-making within interactive systems. This includes but is not limited to, the study of competition and cooperation.
Game theory often examines the limitations of pure theories and identifies situations in which apparently rational actions lead to suboptimal results; i.e. scenarios where rational decisions taken in specific circumstances may not necessarily lead to the best outcomes.
The most common scenario cited to explain the game theory model is The Prisoner’s Dilemma.
The Prisoner’s Dilemma
Let’s get creative; paint a scene in your mind where you and your best buddy got caught robbing a bank.
Now imagine you’re both being interrogated separately in different rooms. Here are the police’s propositions to both you and your friend:
- rat out your friend to leave scot-free, but your friend serves 7 years in jail time;
- if you rat each other out, you both spend 3 years in jail;
- If neither of you rats the other out, you are both imprisoned for 5 years.
While it would be easy to believe that you would not want to rat your friend out for sentimental reasons, the game theory postulates that it may not be the most realistic outcome.
Considering the situation and the number of uncertainties involved, you face more favourable payoffs if you rat on your friend. For instance,
- there is actually the possibility of your friend not confessing and you get to leave scot-free;
- even if your friend confesses, you still get a lesser 3-year sentence than if you had kept quiet;
- you would serve a longer 7-year sentence if your friend betrays you and you don’t.
There are many iterations to this dilemma but they all make the same point — game theory studies decision-making under uncertainty.
Beyond literal games and social engineering, game theory investigates behaviours of market actors, businesses, economies and consumers. Since mathematician John von Neumann and economist Oskar Morgenstern proposed and developed this theory in the 1940s, the concept has been applied in criminology, politics, sociology, psychology, philosophy, and most recently, in blockchain technology and Web3.
Crypto-economics: Game Theory Meets Cryptocurrencies
Game theory, economics, and cryptography are all combined in crypto-economics in a bid to comprehend the incentive structures that underlie distributed blockchain technologies.
Research has shown that distributed peer-to-peer systems are more secure and resilient when rational nodes engaging within a network are understood from a game theory perspective.
The integration of game theory within blockchain technology and the entire Web3 context is what birthed crypto-economics as a concept.
Crypto-economics typically studies the economics of blockchain technology and the potential payoffs that the design and strategy of blockchain protocols may present as a result of the behaviours of concerned players. It also takes the behaviour of external players or agents that are not essentially an integral part of the protocol’s ecosystem but have the potential to join the network with the goal to attack and disrupt it from within.
Crypto-economics does this by studying how network nodes behave depending on the incentives offered by the protocol, taking into account the most logical and likely outcome.
Reaching Consensus
Depending on the consensus mechanism employed, every blockchain network has two major players — the users and the miners/validators.
Validators or miners are saddled with the responsibility of validating transactions and mining the block, while users perform transactions on the blockchain by sending and receiving data and digital assets.
Miners mine these networks for a fee called gas. Whilst this is profitable for them, bad-acting miners can decide to fool the block and not mine it correctly. This is where game theory comes into play.
Game theory is used by consensus algorithms like Proof of Work and Proof of Stake to ensure trustless cooperation.
In Proof of Work networks, new blocks are validated by the miners when they solve an increasingly difficult computational problem. Blocks are mined by solving puzzles that require a lot of resources in the form of computational power and energy consumption.
In like manner, Proof of Stake validators require an investment in the form of a minimum stake to participate in the PoS network’s governance. In return, they receive a portion of the block rewards as compensation for their contribution.
In order to avoid losing their investments, rational actors are motivated to act honestly in a competitive mining environment.
The Consequences of Cheating
Bad-acting miners can cheat by validating invalid transactions or by double-spending. However, they are disincentivized to cheat as they could easily get caught and would lose their resources.
For example, slashing is a form of penalty implemented on PoS networks where bad actors are penalized and fined a percentage of their staked amount for their offence to ensure accountability.
You can therefore compare this scenario to the prisoner’s dilemma discussed earlier. Here, each mining node uses a strategy designed to maximize its own incentivization while ignoring the strategies of other players. Without depending on player trust, such Web3-native distributed networks encourage cooperation between nodes. Players behave in a manner that maximizes their rewards, ultimately keeping the network secure and stable.
Closing Thoughts
Web3 and crypto-economics as a field are still very much in their infancy and there is still plenty of room for development.
We are rapidly approaching a foreseeable future where Web3 and blockchain technology shape our everyday interactions. The underlying mechanics of game theory plays a key role in making that future a reality.
Iterations involving game theory redefine how we view human interaction in relation to economic incentives. As blockchain protocols employ game theory to build decentralized and attack-resistant systems, we will begin to see Web3 and blockchain technology from a more social perspective.
