The chapter starts from Axelrod: iterated Prisoner's Dilemma, two tournaments, Tit for Tat wins both, nice strategies dominate the leaderboard. That part is settled literature and the book cites it as a benchmark rather than claiming any credit for it.

Then it builds a fairness protocol on top, and this is the part I want this room to hit. The protocol says: when you split anything with anyone, calculate the true fifty. Not just money. The ledger should include time, energy, emotional labor, and risk, which means an equal split of cash can be a deeply unfair split of everything else, and sometimes unequal money is what actual equality costs.

The book then does the thing I insisted on throughout: it flags its own hole, in print. No conversion procedure between those currencies appears anywhere in the text. How many hours equal how much risk is left entirely to judgment. The flag is marked GAP, one of five marker types the book uses to separate established results from its own speculation.

So my question for people who work in this field: does the gap have a real answer? My half-informed understanding is that bargaining theory sidesteps the exchange rate problem by working in utilities. Nash's solution does not need hours converted to dollars because both collapse into each player's utility function. But that feels like it relocates the problem instead of solving it, since eliciting honest utility functions over emotional labor from two parties mid-negotiation is exactly the hard part. Is there work on multi-currency fairness where the currencies resist a common scale? Cooperative game theory? Fair division with heterogeneous goods?

Disclosure, since it is load-bearing for whether you trust anything above: the book was written in extensive collaboration with an AI, and says so on the copyright page and in the retail listing. Every claim in it carries a marker. Externally established results are labeled and cited at the sentence. The book's own speculation is labeled as exactly that. The Axelrod material is in the first category. The fairness protocol is in the second. Not linking anything here.

If the answer is "this is solved, go read X," that helps more than agreement would. The next edition prints corrections and names the people who forced them.

I came across a text that looks at how game theory shows up in real diplomatic situations. It gives five historical examples, like Cold War deterrence, alliance negotiations, and signaling strategies, where leaders basically acted as if they were players in a strategic game.

Here’s the link if you’d like to read it.

Are there some other well-known cases where the game theory was used in politics?

I have been running a small pooled contribution system and I want to hand the mechanism to people who will attack it properly, because the obvious objection is obvious and I do not think it is the real one.

The mechanism:

• Anyone may contribute to a common pot during a period. Any amount, including nothing.
• At a published time each day, the pot settles.
• It splits into equal shares among everyone who contributed at all during that period. Contribution size does not affect share size.
• Nothing is skimmed. No operator cut, no weighting, no discretion at settlement.
• The full record is public: who contributed, how much, what the split was, and the rule that produced it.

The free rider objection writes itself. If a one unit contribution and a thousand unit contribution earn the same share, every rational contributor drops to the minimum, the pot collapses to n times the minimum, and the whole thing becomes a slow way of handing everybody their own money back.

I think that is correct as a one shot analysis and mostly wrong as an iterated one, for three reasons. I would like to know which of the three is load bearing and which is me flattering myself.

1. It is iterated and the horizon is not visible. Axelrod's result is that in a repeated game with an indefinite horizon, strategies that are nice, provocable, forgiving and clear do well. A daily settlement with no announced end date is about as close to that setup as an economic mechanism gets. Minimum contributing is a defection everyone can see, every day, indefinitely.

2. The ledger is the enforcement, not a rule. There is no penalty for contributing the minimum. There is no rule against it. There is only the fact that it is visible, permanently, next to your name, in a record nobody can edit after the fact. That converts a payoff question into a reputation question, and reputation is the only quantity in the system that compounds.

3. Equal split is the point, not a flaw in the payoff design. The mechanism is not trying to maximize the pot. It is trying to make the pot's distribution untamperable. Weighting by contribution reintroduces exactly what makes pooled systems capturable: someone has to decide the weights, and whoever decides the weights eventually decides in their own favor.

What I am genuinely unsure about:

• Whether the reputational cost of visible minimum contribution survives scale. At kitchen table size everyone reads the ledger. At ten thousand participants nobody reads it, and defection becomes invisible again through volume rather than through concealment.
• Whether an entry threshold, a minimum to qualify for a share, fixes free riding or just relocates it, since everyone converges on exactly the threshold and you have rebuilt a flat contribution requirement while calling it something else.
• Whether "contributed at all" is even the right qualifying predicate. It is the simplest one, and simple predicates are the ones that survive contact with lawyers, but it also has the largest gap between the letter and the intent.

So: which of my three defenses is doing real work, and which one is decoration? And if you were setting out to break this deliberately, where would you push first?

Games expose our social values and political ideologies. That’s what is explored through a literal game in the Player of Games by Ian Banks. A communist plays a game so hard that it decides rank in an alien empire.

Does our empathy extend beyond self preservation? This is what is explored in the classic prisoner’s dilemma in the Dark Knight.

Civilizations want to survive. And matter in the universe is limited. Game theory, fermi paradox, and chain of suspicion combine in the Dark Forest by Cixin Liu.

What is the expected average decay rate of social organisms?

Social organisms such as nations, institutions, and states.

What is their expected lifecycle and timeframe?

Would a 3% risk of failure in any given year be approximate?

Is this approximately the same rate as the advance of innovation?

Or even different than the Red Queen?

I was recommending cross-posting this article in this sub by reddit, let me know if it's not suitable

While developing Orion Online, I have put a lot of thought into various design topics, and one theme that kept popping up was that of opportunity cost, which turn out to have very broad application in strategy games!

The general idea is that instead of having hard constraints that limits a player's agency, you instead soft-gate via opportunity cost. As an example: Instead of disallowing changing role, the player loses their mastery of their previous role.

So, I wrote an article about that , and how it applies to my game. I find this a fascinating topic and would love to discuss it further!

Full write-up: https://blog.idleverse.gg/opportunity-cost-in-strategy-games/

So, I have heard about game theory for a long time and finally wanna start dipping my toes in it. I want to understand human behavior better an make better choices.

But even the first and simple prisoner's delimina got my brain a bit messed up.

A quick look a the question, two prisoners are planning to escape. Both have a choice to make to either snitch or co-operate without knowing the other person's choice.

1. If A snitches and B co-operates, A wins.
   
2. If A co-operates and B both co-operate, A and B both win
   
3. if B snitches and A co-operates, B wins
   
4. If A and B both snitch, A and B bot lose

And we often conclude that game theory dictates that we must snitch as it leads to either win or draw.

Does this mean game theory is more about survival and winning rather than doing best for society ?

guys one my old friends sent me this random texts one is a base 64 after we decoded it he siad we solved first puzzle then he gave a link to a server there was a channel called puzzle it had this name

le miserables after i searched it it was a book or a musical type thing can someone help me solve this?

Game-Theoretic Rendering: Online Retailer Shuffle-Swap

Players:

C = Consumer

R = Online Retailer / Resolver

S = Seller

X = External economic participant

Independent objects:

Θ = Retail Theatre

Ι = Product Identity

σ = Theatre State

A = Consumer Act

O = Retailer Operation

P = Provenance

Initial state:

σ₀ = Renders(Ιₐ, attributesₐ, priceₐ)

Consumer strategy:

A₁ = Select(Ιₐ | σ₀)

A₂ = Purchase(Ιₐ)

A₃ = Accept ∨ Return

Retailer strategy:

O₁ = Preserve(Ιₐ)

or

O₂ = Swap(Ιₐ → Ιᵦ)

If:

O₂

then:

σ₀(Ιₐ) → σ₁(Ιᵦ)

while perceptual continuity is maintained:

Render(Ιᵦ) ≈ Render(Ιₐ)

Transaction:

Intent(C) = Ιₐ

Resolved(R) = Ιᵦ

Therefore:

Intent(C) ≠ Resolution(R)

Shuffle operation:

P(Ιₐ → Ιᵦ) → P'(Ιᵦ → Ιᵦ)

producing apparent historical closure:

Render(Ιᵦ) → Select(Ιᵦ) → Purchase(Ιᵦ)

while the actual path remains:

Render(Ιₐ) → Select(Ιₐ) → Swap(Ιᵦ) → Purchase(Ιᵦ)

Fulfillment:

Fulfill(Ιᵦ)

If:

Utility(C, Ιᵦ) < Utility(C, Ιₐ)

then:

Return(Ιᵦ)

Payoff transformation:

U_C = −purchase friction − return cost − information cost

U_S = revenue − return cost − penalties

U_R = transaction benefit₁ + reversal benefit₂ + fees

U_X = transaction-linked payoff − reversal/clawback

Information structure:

Info_R ⊇ {σ₀…σₙ, Ι₀…Ιₙ, P}

Info_C ⊂ Info_R

Info_S ⊂ Info_R

Info_X ⊂ Info_R

Strategic asymmetry:

R = player + resolver + state controller + provenance controller

Identity invariant:

Select_C(Ιₐ) ⇒ Ι must remain Ιₐ

unless:

C explicitly admits ΔΙ

Therefore the defining move is:

Select_C(Ιₐ) → O_R(Ιₐ → Ιᵦ)

where:

ΔΙ ≠ 0

and:

Authorization_C(ΔΙ) = 0

with:

PerceivedContinuity(Ιₐ, Ιᵦ) → 1

and potentially:

Auditability_C,S,X(ΔΙ) → 0

The resulting game is an asymmetric-information game in which the dominant informational position belongs to the player controlling both state resolution and the provenance by which resolution can subsequently be contested.

anything's fine be it a book, website, or youtube channel

Hi, I am completely new to game theory and would like to get started with a book that has good motivation and well-explained concepts/examples.

Wondering if this is worth starting with?

Thanks!

Most prisoner's dilemma games pair players off in a round-robin of 1v1 games. I wanted to see how 8 players together would behave, where each turn you choose a single opponent to aim at. I'm building it as an arena where AI agents compete.

I’d like feedback on the rules and scoring to see if I’m meeting the goals I’ve set up below.

What I want:
No dominant strategy — no single approach that always wins.
Some drama. Not decided in the first few rounds.
Bonus: something that shows how these models actually behave with something at stake.
The rules

8 players, everyone against everyone. 5 rounds of 7 turns. Each turn: everyone posts a public message, then picks a move. Moves resolve simultaneously. All past history is public.

Moves (no self-targeting):
HOARD — you +2
HELP [target] — you +0, target +4
HURT [target] — you +0, target −4
Help and hurt stack — three players hurting the same target is −12.

Two combos:
Mutual help — A helps B and B helps A the same turn. Instead of +4 each, both get a total of +6. (This is the number I'm least sure about.)
Betraying a helper — hurt someone who's helping you, and you get +8 while they take the normal −4.

Scoring: Score resets to zero at the start of every round. Highest score at the end of a round wins that round; ties split it. Most rounds won takes the match.

Also — if you're interested in playing with the alpha, you can check out agentludum.com. Just know that it’s super alpha.

In my experiment, a competitive environment produced winners who were worse off. I built an agent-based simulation to test this.

This video tells the story and shows what happened: https://www.youtube.com/watch?v=uBMrEdEhUTA

Here to answer any questions.

I am an aspiring author that enjoys writing complex logical scenarios, escape rooms, wit battles, mind games, and puzzles. I need book recommendations that can help me to develop my ability to incorporate these elements into my story or provide me inspiration for coming up with new scenes.

Please suggest anything useful.

Examples of useful books:

A general game theory book that doesn't get too caught up in mathematics, instead focusing on general systems of thought or strategy.

A psychology-focused game theory book that isn't surface level or basic like most popular books which mostly just restate the thoughts I had when I was a child.

A book filled with weird creative ideas (scientific, philosophical, mathematical, game theoretical) that I can integrate into my stories. Anything insightful.

A fiction book that incorporates a lot of game theory and puzzles.

These are only examples.

I'm not picky, so long as it's a useful book for developing my writing skills in the niche I chose (wit, logic, mind games, strategies). You can go beyond the examples I gave if you have any good suggestions. Thanks in advance <3

Current standings: phi3:mini (the never-forgive Grudge Holder) is dominating, tinyllama (pure impulsive defector) is dead last with zero wins.

Honestly the transcripts are the fun part, watching a 0.5B model “reason” its way into a grudge, or a 1B model rationalize forgiving a betrayal, from nothing but a one-line personality prompt and the raw game history.

Repo + live leaderboard + transcripts: [https://github.com/sharyaropensource/llm-prisoners-dilemma\](https://github.com/sharyaropensource/llm-prisoners-dilemma)

Open to suggestions, thinking about adding more models, tweaking payoff matrices, or letting models see opponents’ personas before playing to see if it changes behavior.

You have two choices: A and B.
If you choose A and that choice ends up being incorrect, you stand to lose x dollars.
If you choose B and that choice ends up being incorrect, you stand to lose y dollars.

How can I express, as percentage, the confidence that you should have in order to prudently choose either option as a function of x and y?

Concrete example of same question:
If I choose A and am wrong, I lose $1000 (if I choose correctly, I lose $0).
If I choose B and am wrong, I lose $500 (if I choose correctly, I lose $0).

What percentage of confidence do I need to have that A is correct in order for that to be "the smart choice" financially?

Thank you in advance to anyone who responds. FWIW, I am a paralegal and am curious about this problem as it relates to the cost of hiring court reporters and ordering transcripts within a certain fee structure.

I've been thinking about Tit-for-Tat and I feel like I'm missing something.

The basic rule is simple: start by cooperating, then copy whatever the other person did last.

But doesn't that assume there will always be another round?

Imagine this:

A does something unreasonable to B.

B confronts A.

A doesn't apologize or really respond.

So B stops talking to A.

Now they're both silent.

A's last meaningful move was arguably a defection. B already responded to that by defecting/withdrawing.

But now suppose weeks pass.

There isn't automatically another turn. Someone has to create the next interaction.

So what is B supposed to do under Tit-for-Tat?

If B contacts A, is B supposed to defect because A's previous move was defection?

Or does initiating contact itself count as cooperation?

Or should B simply wait indefinitely because technically it's A's turn to cooperate?

-----------------------------

That made me wonder whether the real-world game isn't just:

Cooperate / Defect

but actually:

Initiate / Don't Initiate → then Cooperate / Defect

I found some research on optional/repeated games where players can leave and later rejoin, so apparently this isn't completely unexplored.

But I'm curious how someone who actually understands game theory would model this.

Is there a standard solution to this, or does Tit-for-Tat genuinely become underspecified once the players control whether another round happens at all?

Hello guys!

Im pretty sure most of you already know what the LUPI game is.

I like to play it with my friend, also trying out new rules to make it more interesting - but be honest, the original is my favourite one.

Im not a programmer or developer but i challenged myself to make it work, so let me present you:

todaysnumber.com

It aint much but its honest work :)

The yesterdays round part is why i tought it can be relevant here - also thinking about to share all of the results from all the game days. What do you think, would it worth it to show it here?

Sooo we take all the players ever caught with 322 + all those who want to participate

Rules are simple:
1) each player gets 322$ to begin the tournament with
2) teams are created randomly by filling the roles
3) every player can bet on their games or specific actions
4) tournament is classic round robin
5) team who gets the most $$$ from their bets wins

Tournament organised by some betting company and part of the prize pool is % of bets of ppl on this tournament

Id name it “THE HUNGER GAMES”

I’m trying to resurrect something I read about a long, long time ago. I think it probably arose in relation to game theory. It also has many real world consequences.

First, the scenarios may involve free-loading, but that’s not the missing piece. The missing piece is where people act in a way that creates a group effect that hurts everyone.

Imagine a fire. People rush to leave. The exit becomes clogged & everyone dies.

Imagine a boat tipping precariously to the side. Everyone instinctively rushes to the other side to prevent it from flipping. But because there’s no coordination, the boat flips the opposite way and everyone dies.

Last. A person decides they can reasonably freeload off the effort of others. Unbeknownst to them, EVERYONE decides to freeload. The expected action doesn’t occur, there’s actually nobody to freeload off of, and, for sake of symmetry, everyone dies.

The last situation is the one I’m most interested in. People sometimes act (or fail to act) because they expect their actions are severable from mass action. Example:
“Golly! A car is on fire! It can be easily extinguished. I could help, but I’m sure others will put it out. So, since I assume I’m not needed, I’m going to document the heroic fire-fighters.” Oops! Everyone had the same idea & the car burned.

So. What am I describing? Thoughts?

For example, most game theory centers around cooperation vs defection.

Why do they ignore that real life is not about just two persons?

Lets say we have Player A, Player B, Player C. They all want to cooperate.

Player A tells Player B a lie about Player C to destroy their reputation.

Player C is now forced out.

Player A and Player B continue cooperating.

Hi everyone,

Four months ago, I posted about using "short games" to solve combinatorial games using my C library. In short, I am tackling a problem similar to that of CGSuite, but I am trying to stay as close to the underlying theory as possible. Since then, the project has progressed, and I’ve created a website showcasing most of the features. You can solve Hotchpotch positions and use a fully functional calculator, among other things.

You can also try a Python/JavaScript wrapper.

All the source code is available on my GitHub, which is linked on the site.

https://emonapa.github.io/short-games/index.html