How poker and a spaceship imposter game make you better at life.

Von Neumann on how games featuring partial information, chance, and deception will make you a better decision-maker.

My brother and I have been looking for an online game we could play remotely. The search got me wondering if there were games where the skills one builds in making in-game decisions transferred to real-world decisions. If one is going to invest time playing a game, it would be nice if the investment paid off in ways besides the fun of playing.

My brother suggested chess, and I balked. For one, my inner therapist warned me a zero-sum-game where the victor gets IQ-bragging rights could bring up ugly old sibling rivalries.

But beyond that, decision-making in chess is not at all like decision-making in life. John von Neumann explains why.

"Chess is not a game." Poker is.

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20th-century polymath John von Neumann founded modern game theory. When asked if game theory's idea of a "game" was like chess, he said the following:

Chess is not a game. Chess is a well-defined form of computation. You may not be able to work out the answers, but in theory, there must be a solution, a right procedure in any position. Now real games... are not like that at all. Real life is not like that. Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do. And that is what games are about in my theory.~ John von Neumann

Von Neumann gives us a useful constraint on games that might help us make better decisions. Specifically, the gameplay needs three elements to be pedagogically helpful simulations of real life.

  1. Imperfect information
  2. Chance
  3. Deception

Von Neumann pointed to poker as a game that satisfied these constraints, making it an ideal model of human decision-making.

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Why poker, not chess, is a good model of life.

Chess has perfect information.

Chess and games like checkers and Go are perfect information games, meaning both players know the full state of play at any given turn. Perfect information means that at each turn, the player could theoretically find the "best" move. "Best" means the move that will lead to a win (or at least a draw) assuming the player and the opponent are both trying to win. If a player played only the best moves and went first, they would surely win. If they went second, the worst they could do is draw.

Chess playing software can be that perfect player by algorithmically searching through the space of moves and future moves for the optimal decisions. The human mind typically cannot search as efficiently as computers. So human players derive decision-making heuristics that help them find good moves, if not the best moves. A master chess player has learned better mental heuristics than lower-ranked players.

But those heuristics do not translate to making better decisions in life. Those decision-making heuristics are tuned to solve problems where all the information is known. In real-life problems, we never know all the information. We have to reason about uncertainty in terms of chance.

Poker is a partial information game. You know what cards you are holding. You know what cards you and your opponents have played. You do not know what cards your opponents are holding, and you do not know what cards will be dealt going forward.

Chess lacks the element of chance. Poker doesn't.

Chess lacks the element of chance. One might argue that there is an element of chance in how imperfect players guess at what move to make. In precise terms, there is no chance in how the game state changes at each turn. There are no dice rolls that make pieces appear or disappear from the board or change position.

In contrast, in poker, you and your opponents get dealt cards from a shuffled deck. You have some chance of getting a great hand and some chance of getting a weak hand, as do your opponents.

Chance makes it harder to learn from your mistakes and successes. If you lose a chess game, it must be because there were better moves that you didn't make. If you recorded the game, you could rewind the gameplay and pinpoint exactly when you made mistakes. When you can see your mistakes, you can learn from them.

In contrast, it is difficult to determine whether or not a poker loss is due to the quality of your decisions or to the chance elements of the game. A poker world champion can play against a noob and still lose several hands. A new player repeatedly beating a master would never happen in chess.

Humans tend to demonstrate outcome bias, an error made by retroactively evaluating the quality of a decision in terms of the outcome's favorability. When we see someone who is successful in one way or another, we want to conclude the decisions that lead to that success were good decisions. In fact, the successful often argue in favor of this conclusion because it justifies the inequality of their exclusive access to the trappings of success. However, as in poker, a person making poor decisions can still end up with more "winnings" than a more talented decision-maker. You wouldn't take financial advice from someone just because they won the lottery.

The problem is that it is difficult to attribute an outcome's success or failure to chance or the quality of the decision. That makes it hard to learn from our successes and failures.

Poker, unlike chess, features deception.

When our information is incomplete,

  • we don't know what partial information the other players knows,
  • we don't know what they know we know,
  • we don't know if they know we don't know what they know we know, etc.

In other words, partial information creates an incentive for deception; players have the incentive to manipulate the information other people have, so they make decisions that benefit you, and vice versa.

Poker players bluff; they raise the stakes on a poor hand to deceive their opponents into believing they have a good hand. The objective is to convince that opponent to fold, meaning they forfeit their ability to win to limit their losses.

In real life, marketers, politicians, and first dates inflate the benefits and conceal the weaknesses of the "products" they sell. Often, they lie outright to get you to buy/vote/commit in the way they'd prefer.

What if you don’t want to play poker?

The conclusion is that playing poker should make you better at playing life.

However, one problem with poker is that it is a zero-sum game; each hand one player wins, everyone else loses. Real-life “games” players have opponents, but they have allies as well.

To solve that problem, my brother and I eventually settled on Among Us.

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Among Us is a multiplayer game that currently quite popular. Some of the players are Crewmates. The Crewmates are given tasks to complete in the game environment, such as fixing broken systems on a spaceship. Collaborating with Crewmates checks off the collaboration-with-allies box.

The other players are Impostors. Impostors blend in with Crewmates and have the ability to sabotage the systems, identify any other Impostors, and kill Crewmates. Deception is core to the gameplay.

The Crewmates win by completing all tasks before being killed or by finding and eliminating all the Impostors. The Impostors win by killing off enough Crewmates.

Partial information appears in the Crewmates not knowing which players are imposters. Also, each player has a limited cone of vision, which allows players to hide from the view of other players.

Chance is trickier. The Crewmate/Imposter identities are assigned at random at the start of gameplay, but we want to consider chance outcomes during gameplay. There does seem to be chance interactions between that have a big impact on outcomes.

Know any games that better fit the bill? Let me know.