Game Theory

Nash equilibrium explained on one example

“In rock-paper-scissors, for example, the equilibrium tells us, perhaps unexcitingly, to choose one of the eponymous hand gestures completely at random, each roughly a third of the time. What makes this equilibrium stable is that, once both players adopt this 1⁄3 - 1⁄3 - 1⁄3 strategy, there is nothing better for either to do than stick with it. (If we tried playing, say, more rock, our opponent would quickly notice and start playing more paper, which would make us play more scissors, and so forth until we both settled into the 1⁄3 - 1⁄3 - 1⁄3 equilibrium again.) In one of the seminal results in game theory, the mathematician John Nash proved in 1951 that every two-player game has at least one equilibrium.

“It may seem paradoxical, but the equilibrium strategy—where neither player is willing to change tack—is by no means necessarily the strategy that leads to the best outcomes for the players. Nowhere is that better illustrated than in game theory’s most famous, provocative, and controversial two-player game: “the prisoner’s dilemma.”

Prisoners dilemma

My idea: prisoners dilemma should be renamed to Prisoners forced defection (or similar) as defecting is so called dominant strategy, a strategy that in sum of all possibilities give you better outcomes on average. Nash equilibrium in prisoner dilemma is to defect. One of the main insights of the game theory is that equilibriums that are best for each player may not be the best possible outcome (double non-defect).

https://www.lesswrong.com/tag/prisoner-s-dilemma

"The Pris­oner’s Dilemma, as played by two very dumb lib­er­tar­i­ans who keep end­ing up on defect- defect. There’s a much bet­ter out­come avail­able if they could fig­ure out the co­or­di­na­tion, but co­or­di­na­tion is hard. From a god’s- eye-view, we can agree that cooperate- cooperate is a bet­ter out­come than defect- defect, but nei­ther pris­oner within the sys­tem can make it hap­pen. 2. Dol­lar" https://www.slatestarcodexabridged.com/Meditations-On-Moloch

The price of anarchy

“The price of anarchy measures the gap between cooperation (a centrally designed or coordinated solution) and competition (where each participant is independently trying to maximize the outcome for themselves).”

“selfish routing” [in a scenario like car traffic or packets on the internet, when everybody selfishly takes the best route for themselves leading potentially to congestion as this is a best route aka popular] approach has a price of anarchy that’s a mere 4/3. That is, a free-for-all is only 33% worse than perfect top-down coordination. Roughgarden and Tardos’s work has deep implications both for urban planning of physical traffic and for network infrastructure. Selfish routing’s low price of anarchy may explain, for instance, why the Internet works as well as it does without any central authority managing the routing of individual packets. Even if such coordination were possible, it wouldn’t add very much.”

Excerpt From Algorithms to Live By: The Computer Science of Human Decisions Brian Christian This material may be protected by copyright.

Excerpt From Algorithms to Live By: The Computer Science of Human Decisions Brian Christian