Thread: Competition, status & conflict (secondary)
Station · Playable
Your counterpart is a scripted simulation, not a person. The rules, the payoffs and the strategy list are fully visible before you play.
The interactive station needs JavaScript, which is off — nothing is hidden from you because of that. The full explanation below covers everything the station demonstrates.
Points per round (you, partner)
Your move
Partner cooperates
Partner defects
You cooperate
3, 3
0, 5
You defect
5, 0
1, 1
Round 1 of 10 · your points: 0 · partner: 0
The experience
Two players. One choice each round: cooperate or defect. The payoffs sit in
plain view — betrayal pays best, mutual silence pays well, and being the only
cooperator pays nothing. You will play ten rounds against a scripted partner whose
strategy you can inspect before you start. Before you decide what kind of partner you
want to be, it helps to know what people generally do: people cooperate in
this game far more often than the pure self-interest textbook prediction of never.
Averaging across 96 laboratory studies with more than 3,500 players, roughly one
choice in three was cooperative — but the rate swings enormously, from about 4% to
84%, depending on how punishing unilateral cooperation is and how tempting defection
is.Convergent / replicated
What is happening
The dilemma is built into the numbers, not the story. Each player is
individually better off defecting no matter what the other player does — yet if both
defect, both end up worse off than if both had cooperated. Your choice boils down to
weighing the risk of cooperating while the other defects against the temptation to
defect while the other cooperates.Historical / descriptive Every round of the station above puts that
trade-off in front of you again, with your history and your partner's history on the
table.
What this shows
Played once, the game is a trap. Played repeatedly, it becomes a study of trust.
When the same two players meet again and again, cooperation can be
sustained by simple reciprocity. In Axelrod's computer tournaments, the simplest
entry — tit for tat, which cooperates on the first move and then copies whatever the
partner just did — beat fourteen more sophisticated strategies, and the accompanying
analysis showed how reciprocity-based cooperation can get started in a hostile world,
thrive, and resist invasion once established.Supported, with limits You can test this directly: play
the scripted tit-for-tat partner and watch what your own defections cost you two
moves later.
What this does not show
One round of this game does not reveal whether you are a cooperative or a
selfish person. In a classic pair of experiments, simply renaming the identical game
the "Community Game" instead of the "Wall Street Game" shifted cooperation far more
than who was playing, and predictions based on players' real-life reputations
completely failed to pick out who would cooperate and who would defect.Supported, with limits Your
session summary here describes your moves in this session — it is not a personality
reading, and the site draws no conclusions about you.
Research and limitations
The game was invented around 1950 by mathematicians Merrill Flood and
Melvin Dresher at the RAND Corporation, who ran an early experiment having two
colleagues play it one hundred times in a row. Albert Tucker later wrapped the
payoffs in the now-famous story of two prisoners to make the idea accessible to a
psychology audience, and the name "Prisoner's Dilemma" first appeared in print in
Luce and Raiffa's 1957 book.Historical / descriptive
Two honest caveats. First, repetition does not mechanically breed cooperation: the
largest meta-study finds no overall difference between one-shot and finitely repeated
games — repetition helps mainly when cooperating is risky and defecting is not very
tempting. Second, our version tells you upfront that your opponent is a
simulated player, and that itself changes the psychology: experiments show people
extend social rules like promise-keeping to computer partners, but they feel less
committed and break promises to computers more readily than to people. So treat a
session here as practice with the game's logic, not as a measure of how you would
treat a real partner.Supported, with limits The evidence base is overwhelmingly laboratory
experiments with student samples in a handful of countries.
Research drawer — claims, sources and limits
Every highlighted claim above is recorded here with its evidence grade and sources. Grades are per claim; this site never computes an overall truth score.
↩ Each player is individually better off defecting no matter what the other player does — yet if both defect, both end up worse off than if both had cooperated. Your choice boils down to weighing the risk of cooperating while the other defects against the temptation to defect while the other cooperates.
Kuhn, S. "Prisoner's Dilemma." Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/entries/prisoner-dilemma/ · accessed 2026-08-15 Support note: The entry defines the game's payoff structure (defection dominant for each player, mutual defection Pareto-inferior to mutual cooperation) — the definitional tension the claim describes.
Mengel, F. (2018). Risk and Temptation: A Meta-study on Prisoner's Dilemma Games. The Economic Journal, 128(616), 3182-3209. doi:10.1111/ecoj.12548 https://repository.essex.ac.uk/20382/1/Mengel-2017-The_Economic_Journal.pdf · accessed 2026-08-15 Support note: Read the accepted-manuscript PDF: the paper identifies 'risk' (loss from cooperating unilaterally) and 'temptation' (gain from defecting on a cooperator) as the two defining properties of the prisoner's dilemma, matching the claim's framing of the choice.
↩ people cooperate in this game far more often than the pure self-interest textbook prediction of never. Averaging across 96 laboratory studies with more than 3,500 players, roughly one choice in three was cooperative — but the rate swings enormously, from about 4% to 84%, depending on how punishing unilateral cooperation is and how tempting defection is.
Mengel, F. (2018). Risk and Temptation: A Meta-study on Prisoner's Dilemma Games. The Economic Journal, 128(616), 3182-3209. doi:10.1111/ecoj.12548 https://repository.essex.ac.uk/20382/1/Mengel-2017-The_Economic_Journal.pdf · accessed 2026-08-15 Support note: Read the accepted-manuscript PDF directly: meta-study of 96 prisoner's dilemma studies, >3,500 participants across 6 countries; 'Average cooperation rates across these 96 studies range from 0.04 to 0.84 with a mean of about 0.35'; the risk index best explains one-shot variation and temptation best explains finitely repeated games.
Sally, D. (1995). Conversation and Cooperation in Social Dilemmas: A Meta-Analysis of Experiments from 1958 to 1992. Rationality and Society, 7(1), 58-92. doi:10.1177/1043463195007001004 https://doi.org/10.1177/1043463195007001004 · accessed 2026-08-15 Support note: Opened the SagePub abstract page: meta-analysis of 35 years (1958-1992) of published PD/social-dilemma experiments concluding that 'a model of pure self-interest is usually inconsistent with the results of experimental decision making,' and that communication markedly raises cooperation — supporting the 'more cooperation than self-interest predicts' half of the claim.
↩ When the same two players meet again and again, cooperation can be sustained by simple reciprocity. In Axelrod's computer tournaments, the simplest entry — tit for tat, which cooperates on the first move and then copies whatever the partner just did — beat fourteen more sophisticated strategies, and the accompanying analysis showed how reciprocity-based cooperation can get started in a hostile world, thrive, and resist invasion once established.
Axelrod, R., & Hamilton, W. D. (1981). The Evolution of Cooperation. Science, 211(4489), 1390-1396. doi:10.1126/science.7466396 https://doi.org/10.1126/science.7466396 · accessed 2026-08-15 Support note: Read the full-text PDF (mirror on Axelrod's University of Michigan site): reports the iterated-PD computer tournament in which tit for tat ('cooperate on the first move, and thereafter do what the opponent did on the previous move') won against 14 other submissions, and develops the evolutionarily-stable-strategy argument that reciprocity-based cooperation can get started, thrive against varied strategies, and resist invasion.
Rapoport, A., & Chammah, A. M. (1965). Prisoner's Dilemma: A Study in Conflict and Cooperation. Ann Arbor: University of Michigan Press. https://press.umich.edu/Books/P/Prisoner-s-Dilemma · accessed 2026-08-15 Support note: Opened the University of Michigan Press catalog page, which confirms bibliographic details and describes the book as 'an account of many experiments in which Prisoner's Dilemma was played,' examining when players trust or betray — documenting the large-scale repeated-play experimental tradition that Axelrod's tournaments later formalized (Anatol Rapoport, its first author, submitted the winning tit-for-tat strategy).
↩ One round of this game does not reveal whether you are a cooperative or a selfish person. In a classic pair of experiments, simply renaming the identical game the "Community Game" instead of the "Wall Street Game" shifted cooperation far more than who was playing, and predictions based on players' real-life reputations completely failed to pick out who would cooperate and who would defect.
Liberman, V., Samuels, S. M., & Ross, L. (2004). The Name of the Game: Predictive Power of Reputations versus Situational Labels in Determining Prisoner's Dilemma Game Moves. Personality and Social Psychology Bulletin, 30(9), 1175-1185. doi:10.1177/0146167204264004 https://doi.org/10.1177/0146167204264004 · accessed 2026-08-15 Support note: Opened the PubMed abstract via NCBI E-utilities: two experiments (US undergraduates; Israeli pilots nominated as most likely cooperators/defectors) found the Wall Street vs Community Game labeling manipulation 'exerted far greater impact on the players' choice to cooperate versus defect' than reputational factors, and reputation-based predictions failed to discriminate cooperators from defectors.
Mengel, F. (2018). Risk and Temptation: A Meta-study on Prisoner's Dilemma Games. The Economic Journal, 128(616), 3182-3209. doi:10.1111/ecoj.12548 https://repository.essex.ac.uk/20382/1/Mengel-2017-The_Economic_Journal.pdf · accessed 2026-08-15 Support note: Read the accepted-manuscript PDF: cooperation rates across studies vary from 4% to 84% mostly as a function of the payoff parameters (risk and temptation) rather than who is playing — supporting the point that a single observed choice reflects the situation's structure at least as much as the person.
↩ The game was invented around 1950 by mathematicians Merrill Flood and Melvin Dresher at the RAND Corporation, who ran an early experiment having two colleagues play it one hundred times in a row. Albert Tucker later wrapped the payoffs in the now-famous story of two prisoners to make the idea accessible to a psychology audience, and the name "Prisoner's Dilemma" first appeared in print in Luce and Raiffa's 1957 book.
Kuhn, S. "Prisoner's Dilemma." Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/entries/prisoner-dilemma/ · accessed 2026-08-15 Support note: The entry states that in early 1950 Flood and Dresher had two professional colleagues play a game with the PD payoff structure one hundred times in succession; that the prison-sentence story is due to Albert Tucker, who wanted to make the ideas accessible to an audience of Stanford psychologists; and that the label 'Prisoner's Dilemma' first appears in Luce and Raiffa's 1957 work.
↩ our version tells you upfront that your opponent is a simulated player, and that itself changes the psychology: experiments show people extend social rules like promise-keeping to computer partners, but they feel less committed and break promises to computers more readily than to people. So treat a session here as practice with the game's logic, not as a measure of how you would treat a real partner.
Kiesler, S., Sproull, L., & Waters, K. (1996). A prisoner's dilemma experiment on cooperation with people and human-like computers. Journal of Personality and Social Psychology, 70(1), 47-65. doi:10.1037/0022-3514.70.1.47 https://doi.org/10.1037/0022-3514.70.1.47 · accessed 2026-08-15 Support note: Opened the PubMed abstract via NCBI E-utilities: in a PD with disclosed computer partners, most participants proposed cooperation after discussion and kept promises with a text-only computer as much as with a person, but less with a more human-like computer; commitment was stronger toward human partners, and people broke promises to computers more readily than to people.