The Prisoner’s Dilemma is a simple game theory problem that shows how two people, each trying to help themselves, can both end up worse off than if they had worked together. The concept is explained through a story about two suspects who are questioned separately, and their choices lead to different prison sentences.
The idea first appeared in a 1950s study by Merrill Flood and Melvin Dresher. Later, Albert W. Tucker named it the “prisoner’s dilemma” and connected the story to the math behind it. This example became a useful way to show how personal interests can conflict with what is best for a group.
The usual story is that two people are arrested and kept in separate rooms. Each person can either stay silent or betray the other. If one betrays and the other stays silent, the betrayer goes free and the silent one gets a long sentence. If both stay silent, they both get a short sentence. If both betray, they both get a medium sentence. The exact numbers can change, but the order of outcomes stays the same: betraying while the other stays silent is best for one person, both staying silent is best for both together, and both betraying is worse than both staying silent.
For each person, betraying the other seems like the safer option. No matter what the other person does, betraying either lowers your sentence or keeps it the same compared to staying silent. In game theory, betrayal is called a dominant strategy for each player, and when both betray, it is a Nash equilibrium. This means that once both have chosen to betray, neither can do better by changing their choice.
If the same people have to make this choice many times, the situation changes. In repeated games, cooperation can become a steady choice because players can reward each other for working together and punish betrayal over time. Strategies that remember what happened before, like tit-for-tat, can lead to long-term cooperation, even though a one-time game usually leads to betrayal.
The Prisoner’s Dilemma helps explain real-life situations where acting for yourself in the short term can hurt the group in the long run. Economists use it to look at price wars and public goods. Political scientists use it to study arms races and trade disputes. In crypto and blockchain, similar problems happen when people can benefit themselves but hurt the whole network. When people interact many times and reputation is important, the reasons to cooperate usually increase.
Researchers adjust the rules to model different situations. They might change the rewards, allow more than two players, or let players talk to each other. These changes show that the basic Prisoner’s Dilemma is just a simple model. Real people may act differently because they care about fairness, trust, or future relationships, and real situations often have more information and social rules.
Some critics say the model is too negative about how people interact because it leaves out social rules and other reasons people act besides self-interest. Others point out that the numbers used in examples are often picked to prove a point, so they might not fit real life. Even so, the scenario is still helpful for understanding how incentives affect choices.
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