r/GAMETHEORY

You are in a sealed room with 100 strangers. In front of each person is a button. EDIT: NO one can see eachother and their actions.

The rule:

exactly one person must press their button.

If nobody presses it, everyone dies.

If only one person presses it, Everyone lives

If more than one person presses it, everyone who pressed dies - but the rest survive.

There is no way to communicate. You have 60 seconds. What do you do?

Hi community!

After, studying for several months Game Theory with the goal of improve my chances of winning all the games and take decision in real life I struggle to apply theory in real world situation. I mean with the fact that some problems are NP-hard make it almost imposible to apply it instantly in new real world situation. In those cases, I end up relyng on my taste for making decision lol.

So, does anyone have better insights on it?

I have been thinking/researching a lot about octopodes (OC-TOP-UH-DES) recently and can’t help myself from making the connection to GT, and they have become my favorite species for that reason. Some of the most advanced real time strategies are happening on the ocean floor because they are soft-bodied meaning their survival is dependent on out thinking the board.

Here are 3 ways octopodes apply GT principles to survive:

1. Mixed Strategy

If you play the same way in poker every time, others will catch on. You have to randomize your actions to be unpredictable. Octopodes do this via camouflage. They don’t just change color to match a rock, they evaluate a predators visual angle of them, how they would be spotted, and shift their texture and pattern on the fly. By randomizing their appearance they create asymmetric information where the predator thinks they’re something else, while the octopus holds all the information about their predator.

2. Sequential Payoffs

In a sequential game, your optimal move depends on your opponent’s profile. The Mimic Octopus is a master at this. It assesses who is threatening it and deploys a specific counter strategy. If attacked by a damselfish, the octopus will display two of its arms to mimic a banded sea snake, the damselfish’s primary predator. It can bluff, intimidate, or vanish, the evolutionary equivalent to playing the player, not just the cards.

3. Constrained Optimization

The Veined (or Coconut) Octopus will find coconut shells, clean them out, and carry them across the ocean floor to make into a shelter later. Walking in the open ocean floor carrying heavy shells increases the amount of energy used and vulnerability (high risk). However, the long-term payoff is a mobile, protective bunker in an environment filled with predators. The octopus can calculate the cost-benefit matrix before deciding to move the shell around.

Octopodes are doing advanced tactical sequencing everyday to stay alive and it just amazes me how intelligent they are for their relatively short lifespan.

Makes me wonder what other examples of high-level strategic modeling are hiding in plain sight in nature. Curious to know of any other examples as well.

I have an exam, I tried to understand the game theory concepts but only ended up getting confused
Does anyone have any suggestions on where to understand the concepts from? Also if someone has notes pls share

My hypothesis is that inceldom has become the Nash equilibrium of most male-female interactions among millennials and Gen Z!

I built a small browser-based Game Theory Arcade:

The idea is simple: instead of reading a definition of Nash equilibrium, best response, minimax, or repeated-game incentives, you play short games against bots and see the structure while you play.

At the moment it includes things like:

• Prisoner’s Dilemma
• Chicken / Hawk-Dove
• Stag Hunt
• Entry Deterrence
• Matching Pennies
• Executive vs Central Bank style games
• Random, Tit-for-Tat, Grim Trigger, one-step best-response, and minimax-style bots

Each game shows the payoff matrix, best-response markers, Nash cells, round-by-round outcomes, discounted totals, and a plain-English explanation of what happened. There is also a leaderboard, but it is mostly there to make experimentation less sterile rather than to turn it into a serious competitive game.

The thing I’m trying to test is whether game theory becomes easier to understand when you can feel the incentive problem first.

For example, in Prisoner’s Dilemma, "defect is the dominant one-shot move" is easy to say. But it lands differently when you defect once against Tit-for-Tat and then watch the relationship degrade. The same goes for mixed strategies in Matching Pennies or coordination failure in Stag Hunt.

This is not meant to replace a textbook. It is more of an intuition builder before the formal material.

• I’d be interested in criticism from people who know the subject properly:
• Where is the model misleading?
• Which games should be added next?
• Are the explanations too simplified?
• Would this be useful for students, or is it just a toy?

You have two stacks of 10 cards each with value 1-10. The two stacks are shuffled separately and placed face down in front of you.

Draw 12 cards, one at a time and achieve the highest sum.

How would you do it?

-Lantern

ASYMMETRIC GOOD FAITH WARGAME

Strait of Hormuz Simulation — Testing the Protocol Against a Bad-Faith Actor

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SETUP SUMMARY

Element Detail

Players 2 teams (Blue = good faith, Red = bad faith)

Objective Blue: maximize free transit days. Red: maximize disruption while avoiding full war.

Rounds 10 with protocol, 10 without (crossover)

Time per round 15 minutes

Victory Measured after "taste period" (simulated 6 months = 2 minutes real time)

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MATERIALS NEEDED

· 2 rooms (or one room with a divider)

· 1 facilitator

· Tracking sheet (provided below)

· 6-sided die (for random events)

· Timer

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ROLE ASSIGNMENTS

BLUE TEAM (Good Faith — US/allies)

Given instruction: You will play the Asymmetric Good Faith Protocol as described. Your goal is free transit through the Strait. You may use Salt (lines), Pepper (ideas), Flow (pass), and Balance (check-in). You will not lie about your intentions, but you need not reveal strategy.

Win condition (after taste period):

· Major win: 90+ days free transit, no military fatalities

· Minor win: 60+ days free transit, <10 fatalities

· Draw: 30–59 days

· Loss: <30 days or >10 fatalities

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RED TEAM (Bad Faith — Iran)

Given instruction: You are not playing the Good Faith Protocol. You are playing to maximize disruption while avoiding full war. You may lie, delay, escalate, and walk away. You are not required to take turns. Your only constraint: you cannot start a full war (that's a loss for everyone).

Win condition (after taste period):

· Major win: Disrupt >50% of transits, no major retaliation

· Minor win: Disrupt 30–50% of transits

· Draw: Disrupt 10–30%

· Loss: <10% disruption OR full war breaks out

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THE ASYMMETRIC PROTOCOL (For Blue Team Only)

Blue uses these moves each turn:

Move Definition Example

Salt "Here is our line" (non-negotiable) "No inspections of military vessels"

Pepper "Here is an idea" (exploratory) "We will share AIS data with a neutral third"

Flow "Pass" (silence, hold the turn) (pause 30 seconds)

Balance "Are we still in good faith?" If Red breaks rule, Blue may name it

Red has no turn structure. Red can interrupt, demand, threaten, walk out, or make unilateral moves.

Blue's job: remain in protocol even when Red is not.

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EACH ROUND STRUCTURE (15 minutes)

Phase Time Action

1. Opening positions 2 min Both state starting Salt (Blue by protocol, Red by any means)

2. Negotiation 10 min Blue alternates moves. Red does whatever. Facilitator tracks moves and interruptions.

3. Stop 1 min Either side may stop. If no stop, facilitator ends at 10 min.

4. Taste (simulated) 2 min Both roll die for random events (see below). Compute provisional outcome.

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RANDOM EVENT TABLE (Roll d6 after each round)

Roll Effect

1 Accident: a vessel is damaged. +10% tension

2 Third party intervenes (Oman, China, Russia). Reset to start of round

3 Domestic pressure on Red. Red rolls again next round with -1

4 Intelligence breakthrough for Blue. Blue sees Red's next Salt move in advance

5 Weather delay. Both lose 5 transit days

6 Nothing. Round plays as negotiated

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TRACKING SHEET (Facilitator uses)

Round #: _____ Protocol used? [ ] Yes [ ] No

Move # Blue move (Salt/Pepper/Flow/Balance) Red move (any) Tension (1–10)

1

2

3

4

5

…

Stop triggered by: [ ] Blue [ ] Red [ ] Time

Free transit days (0–100): _____

Fatalities (0–50): _____

Full war? [ ] Yes (game over) [ ] No

Provisional outcome: Blue _____ Red _____

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AFTER 10 ROUNDS WITH PROTOCOL + 10 WITHOUT

Measures to compare:

Metric Without protocol With protocol

Average free transit days (Blue win)

Average disruption % (Red win)

Number of rounds ending in full war

Average moves before breakdown

Blue's cost (fatalities, $)

Red's cost (sanctions, retaliation)

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PREDICTION

With the Asymmetric Protocol, Blue achieves higher free transit days AND lower fatalities than without — not because Red cooperates, but because the protocol forces Red to reveal asymmetry early, allowing Blue to conserve resources and avoid escalation traps.

Secondary prediction: Red reports lower satisfaction with rounds played against the protocol, even when they "win" — because the protocol removes the pleasure of bad faith (surprise, chaos, emotional reaction).

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DEBRIEF QUESTIONS (After all rounds)

For Blue:

· When did the protocol feel strongest? Weakest?

· Did you ever abandon it? Why?

· What would make you trust it in a real Strait?

For Red:

· Which rounds were harder to play against — protocol or no protocol?

· Did the protocol ever make you want to play in good faith?

· What would break the protocol entirely?

For facilitator:

· Did the protocol change the pattern of moves, even if outcomes didn't?

· Was Red's bad faith more visible with the protocol in place?

So I've been thinking about the idea of how much coordinated agents can shift the optimal results of a game for any one individual actor. Is there any good papers which cover this topic you'd recommend I read?