What is game theory? Game Theory in Cryptocurrency

What is game theory?

Game theory is the study of the rational decisions of players in a system (games, scenarios, etc.). It studies tactical situations in which players choose different actions to maximize results. Originally developed as a tool for the study of behavioral economics, game theory today is used in many sciences, from biology to philosophy, psychology, and logic. And incentives can lead to active, honest, and predictable players. The Game Theory model consists of at least three components. 

• Player: The one who plays the decision-making role. Examples: Director, Social Member, SKLockan-Network Button, etc.
• Strategy: Some of the decisions that players can make. This strategy is a change in the behavior that players perform while considering the potential strategies of other players. Follow violations of network protocols, regulations, or fraudulent dishes.
• Result: Fully combined with other actors in the system to implement the policy. With the right incentives, you can repeat certain actions to achieve the same results. For example, fines encourage drivers to follow traffic rules and reward those who mine a certain amount of Bitcoin. This encourages you to maintain your network and stick to the protocol rather than breaking it.

See also: What Is Airdrop? The Potential Of Airdrop And Retroactive In The Cryptocurrency Market

Description: Game Theory via Prisoner Dilemma

Prisoner’s Dilemma is a zero-sum game in game theory.

Assuming A and B are arrested for shoplifting at the grocery store and are in the process of being investigated, it has been discovered that both have committed many serious crimes in the past. Police suspect both men were involved in a bank robbery. During the investigation, the police interrogated each one by one and made some of the same suggestions for both:

• First, if you both remain silent and don’t tell the other, you’ll both go to jail for two years for stealing.
• Second, if one of them testifies to the other and the other is silent, the person who testifies will be exonerated and released, while the other will receive an eight-year prison sentence.
• Third, if they both told each other, they would each receive four years in prison.

In this case, each prisoner has two options:

• Work with the other and keep quiet.
• Betray and tell the other.

The outcome of each choice depends on the other person’s choice. However, no one knows the other’s choice. If they can talk to each other, they’re not sure they can trust each other. From there, the reward matrix can be built as follows:

From an optimal point of view for both of you, the best outcome would be for both of you to work together, when the time spent in prison was only 2 years. Any other option would result in a longer prison term for the two of you. However, since each pursued his or her selfish interests, both were sentenced to longer sentences. Everyone wants to be good for themselves, regardless of others’ condition.

Therefore, the results of this game are not optimal for both. Everyone has the incentive to tell everything. That’s why this game is called a problem.

Game Theory in cryptocurrency

When applied to cryptocurrencies, Game Theory models play an important role in designing a secure economic system (such as Bitcoin). The creation of Bitcoin as a Byzantine Error-Tolerant System (BFT) is the result of a harmonious combination of cryptography and Game Theory.

The use of Game Theory in the context of cryptocurrencies has created the concept of Crypto Economics. Basically, it is the study of the economics of blockchain protocols and the potential consequences from the design of these protocols can bring (as a result of the behavior of the participating component). Crypto economics also looks at the behavior of “external actors” (not really part of the ecosystem but can join the network) in order to cause disruption from within. In other words, Crypto Economics studies the behavior of network Nodes based on the incentives provided by the protocol, considering the most rational and most likely decisions.

Since the Bitcoin blockchain is designed as a distributed system with multiple nodes dispersed in different locations, the authentication of transactions and blocks needs to be based on the consensus of these nodes. However, these nodes can’t really trust each other. 

One of the most important features of the Bitcoin network that helps protect it from malicious activity is the Proof of Work consensus algorithm. This algorithm applies coding techniques that make the mining process very expensive, creating a highly competitive mining environment. Therefore, the architecture of PoW-based cryptocurrencies encourages mining nodes to operate honestly (nodes will not risk losing resources that have been invested). On the contrary, any malicious activity that is not prompted is quickly punished. Mining nodes with dishonest behavior ѕ will lose a lot of money ᴠà ѕ will be removed from the network. Therefore, the most reasonable determination ᴠà can be made by miners is to act honestly ᴠà keep the blockchain safe. 

This is how the Bitcoin network can avoid malicious activity, and a blockchain can prevent being broken by dishonest nodes.

See also: What Is Market Cap? Explain Crypto Market Capitalization In 2 Minutes

Conclusion

The general application of Game Theory is to model and test how people behave and make decisions based on rational judgment. Therefore, game theory models must always be scrutinized when designing distributed systems.

Thanks to a balanced combination of cryptography and Game Theory, the Proof of Work Consensus algorithm has been able to create the Bitcoin blockchain as a decentralized economic system, highly resistant to attacks. The same is true for other cryptocurrencies, and the concepts of game theory also apply to PoS-based blockchains. The main difference here is how a Proof Of Stake blockchain processes transactions and conducts block validation.

However, the level of security and resilience of the blockchain depends on its protocol and is directly related to the number of people involved in the network and large distributed networks that are more reliable than small networks.