Published on 8/31/20, 11:16 AM
Game theory is highly relevant to cryptocurrencies and is often an overlooked aspect of platforms, despite playing a vital role in their security and sustainability.
A renewed vigor in game theory development and analysis has coincided with expanded interest and focus on developing cryptocurrency platforms.
This has led to a interesting new field called cryptoeconomics, and the fundamental role that classical and contemporary game theory models play in it is vital to understanding the primary dynamics of interactions between players in cryptocurrency platforms.
In order to be able to fully comprehend the role that game theory plays in cryptocurrency platforms, you need to actually understand what exactly game theory is and how it can be applied to a vast array of scenarios.
Simply put, game theory is the study of logical decision making made by players within the defined parameters of a system (game, scenario, etc). It uses mathematical models and can be applied to economics, psychology, logic, computer science, distributed systems, and more. Game theory can be seen as a microcosm of human behavior under set circumstances wherein certain incentive structures and mechanisms can lead to predictable and honest behavior by players.
In a typical game theory scenario, there are 3 primary components.
Players are the users that make decisions. Strategies are the maneuvers that players make while simultaneously taking into account potential strategies of other players. The outcomes are the result of the players’ moves within the system, and with the right incentive mechanisms, can be driven to a certain direction or played out repeatedly with similar outcomes.
To better demonstrate this, the prototypical example of game theory that you probably have heard of is referred to as the Prisoner’s Dilemma. In this scenario, there are two prisoners being interrogated separately for a crime that they are both equally guilt of.
Let’s call them Alice and Bob…
Both Alice and Bob are offered an opportunity to confess and receive a reduced sentence. The outcome of this scenario can play out in 4 ways, with both Alice and Bob having to make one of two possible decisions, either confess or don’t confess. This results in the 4 possible outcomes laid out in the table below.
As you can see, the overall solution with the least jail time for both prisoners is for both prisoners to remain silent and not confess. This option is highlighted in blue in the bottom right corner. However, this outcome is considered unstable as it makes an assumption that both prisoners will knowingly leave a better deal on the table where they could potentially receive 0 years and be set free if they confess and the other prisoner does not.
Consistent game theory model outcomes and behavioral psychology tell us that this outcome is highly unlikely, as rational players will inherently betray the other due to self-interests.
In game theory, the solution to a game where each player chooses their optimal strategy given the strategy was chosen by the other and they have nothing to gain by shifting their strategy is known as Nash Equilibrium.
This is a stable state and is represented in the top left corner of the chart. In this outcome, Alice and Bob are both making the best decisions that they can while taking into account the other player’s decision.
The Prisoner’s Dilemma is a non-cooperative game theory model and a classic example of a non-zero sum game situation. A non-zero sum game is a situation where interacting parties’ aggregate gains and losses can be more or less than zero. This results in the ability of non-zero sum games to be either non-competitive or competitive as compared to zero-sum games that are strictly competitive.
The example of the Prisoner’s Dilemma can be used in a variety of real-world situations to demonstrate cooperative behavior between players. In distributed systems, this concept is paramount to maintaining trustless consensus models and has important ramifications when applied to cryptocurrencies in the context of crypto economics as you will see.
Cryptoeconomics can be defined as the combination of cryptography, economics, and game theory incentive models incorporated into distributed blockchain protocols in order to create a secure, stable, and sustainable system.
It is a very new concept, but when you really dig deep into the functionality of cryptocurrency platforms, you will see how important it is to mitigating malicious actors and promoting honest, trustless behavior across the network.
The best example to understand the role of game theory and cryptoeconomics in cryptocurrency platforms is Bitcoin. In order for distributed blockchain networks like Bitcoin to remain secure and have the ability to reach the necessary consensus on the blockchain, they need to remain Byzantine Fault Tolerant.
For the system to remain Byzantine Fault Tolerant, the decentralized nodes have to come to a majority agreement on the current state of the blockchain without trusting each other.
This is very difficult to accomplish and is outside of the scope of the employed cryptography, which is used to cryptographically link each block of the blockchain, not determine whether the transactions contained within the blocks are valid or which of 2 competing chains is the valid one.
Bitcoin solves this problem through its Proof-of-Work consensus model. The model works where miners need to solve computationally intensive mathematical problems in order to win the reward for mining the next block.
This solution needs to be verified by the other miners and the inherent cost of the process is electricity, a real-world asset with a financial value. The resulting chain becomes secure and very costly to manipulate or attack. The larger and more decentralized the network becomes, the increased difficulty in accomplishing an internal or external attack.
Incentive structures predicated on game theory mechanisms come into play in order to encourage the players (users and miners) in the system to act honestly. Additionally, some abstract concepts within game theory work subtly in the background.
Starting with miners, the obvious economic incentive stems from the block reward if they solve the next round of mining for the next block. The reward in Bitcoin is currently 12.5 BTC. This is important because since the miners are receiving the reward in Bitcoin, it is in their best interest for the value of Bitcoin to increase and the network to remain valid and secure.
They actively spend resources (electricity) to have a chance to win the block and thus, their efforts will be a sunk cost if they use malicious actions to attack the network and jeopardize the value of the reward. It becomes increasingly more costly to act dishonestly than it does to act honestly within the system.
This creates a positive feedback loop where miners have a consistent positive incentive to maintain the valid blockchain and mitigate against malicious actors, resulting in a secure network.
Miners can act maliciously in a number of ways, including adding invalid transactions into blocks or mining on top of invalid blocks to gain more BTC. However, this is where game theory mechanics come to the rescue. Invalid blocks will be rejected by the majority of miners in a coordination game format where it is in the best interest financially of miners to remain with the majority and not attempt to create invalid blocks due to the inherent and increasing cost associated with doing so.
The resulting conclusion from this is that the Bitcoin blockchain is constantly in a self-reinforcing Nash Equilibrium state. The system is Byzantine Fault Tolerant due to the majority of miners working in coordination to achieve and maintain the most stable state of the network at all times.
With regards to users, their preference for the longest chain (and the most secure) is a result of a concept known as Bounded Rationality. Basically, users are familiar with the main chain and switching chains creates unnecessary complications. Maybe irresponsible, but most users assume that incentive mechanisms are working correctly to keep miners’ power in check.
Despite the incentive structures and game theory mechanics driving honest behavior in the Bitcoin network, there are some important issues that are widely recognized. Centralization of mining as a result of mining pools has led to concerns that the reinforcing Nash Equilibrium of the system can be compromised through a 51% attack.
This is where malicious miners control enough of the network hashing power to fork the blockchain, overriding the coordination game played out by a decentralized network of miners. Due to this, some view incentive mechanisms as not particularly necessary or only necessary as a last resort of cryptocurrency platforms due to the complications in system logic that they create.
The empirical problem laid out by critics is that the success of game theory models in these platforms cannot be determined academically, only through practice. Some of the assumptions made by game theory models in cryptocurrency platforms revolve around a specific threshold of people acting honestly or dishonestly.
Predicating platform security on implied assumptions of human behavior can be risky, especially when there is no precedent for the technology or models being implemented.
Bitcoin as a decentralized network is built on the uncoordinated choice concept where coordination between parties is limited by the size of parties interacting with each other. Centralized mining pools do not follow this concept and therefore create a viable security concern.