Game Theory in Psychology

What are the components of a game?

The components that are necessary to a game, according to game theory, are:

Game Theory Examples: Classic Games

Cooperative vs. non-cooperative game theories

Cooperative and non-cooperative game theories are the most common types of game theory.

Cooperative game theory studies how groups, or coalitions, interact. Players can make binding agreements, and the analysis concerns how the group divides the known payoffs. It is a game between groups rather than between individuals.

Non-cooperative game theory is the dominant strand. Players cannot make binding agreements, so each pursues personal goals given only the available strategies and the outcomes of each combination of choices. Rock-paper-scissors is a real-world example.

Zero-Sum, Non-Zero-Sum, and Sequential Games

In a zero-sum game, one player’s gain is exactly another’s loss, as in poker among friends. There is no scope for mutual benefit.

Non-zero-sum games allow outcomes where all players gain or all lose. Most social life works this way, which is why these games can model cooperation and its failures.

Games can also be simultaneous or sequential. In a simultaneous game, players move at once without knowing each other’s current choices. In a sequential game, players move in turns and see what came before, which brings in threats and reputation.

Types of game strategy

Below are some of the game strategies that players can use according to game theory:

What is Nash Equilibrium?

The Nash Equilibrium is named after the mathematician John Nash. He proved that every finite game has at least one equilibrium, though sometimes only in mixed, or randomized, strategies (Nash, 1950).

In a Nash Equilibrium, no player can improve their own payoff by changing strategy alone, given what everyone else is doing. Each player’s choice is a best response to the others’. So nobody has a reason to move.

Considering the Prisoner’s Dilemma game theory, we can work out the Nash Equilibrium of the choices both prisoners make:

• The best option for prisoner one, if prisoner 2 confesses, is to also confess because if they deny the crimes, prisoner one will receive a 9-year sentence.

• The best option for prisoner one if prisoner 2 denies the crimes is to confess, because prisoner one then goes free instead of serving 2 years.

Thus, confessing is the best choice whatever the other prisoner does, so the only Nash Equilibrium is for both prisoners to confess.

Yet this equilibrium is not the best outcome. Both prisoners serve five years, when mutual silence would have cost them only two. A Nash Equilibrium can leave everyone worse off, because no single player can gain by moving away from it alone.

A game can have one Nash Equilibrium, several, or none in pure strategies. The Prisoner’s Dilemma has just one: both prisoners confess.

In simultaneous games that are repeated over time, one of the multiple equilibria is often reached through convention, communication, or trial and error.

The Nash Equilibrium is also a ‘no regrets’ outcome. Once a player has decided, they would not change their choice, given what the others did. Equilibrium is usually reached over time, and once found, it is not deviated from.

To test for one, imagine taking a different move. If it would not help, you have found a Nash Equilibrium.

How does game theory relate to psychology?

Game theory also applies to human psychology. It predicts what a purely rational, self-interested player should do, so any departure from that prediction becomes a measurable psychological finding.

By using methods such as eye trackers, electroencephalography (EEG), and galvanic skin response (GSR), researchers can understand the decision-making process within games.

Emotion and Mood

Galvanic skin response (GSR), the skin’s electrical conductance, rises with emotional arousal. One study measured it while 30 undergraduates played the Ultimatum game (van ’t Wout et al., 2006).

Arousal was higher for unfair offers and linked to rejecting them. This held only for offers from human partners, not computers.

That matters because rejecting an offer is the ‘irrational’ move, since any money beats none. Emotion may override the calculation.

Mood matters too. Harlé and Sanfey (2007) induced sadness with short movie clips before participants played the Ultimatum game.

Sadness interacted with offer fairness: the sadder the participant, the fewer unfair offers they accepted.

Emotions carried into a game shift behavior, even when they are irrelevant to the transaction. Even subtle moods can bias decisions.

Brain Activity

Babiloni et al. (2007) used EEG to record brain activity while pairs played the Prisoner’s Dilemma. This hyperscanning records both players’ brains at the same time. Activity in the anterior cingulate cortex, an area linked to emotional control, was associated with the likelihood of betrayal.

Sanfey et al. (2003) scanned players during the Ultimatum game. Unfair offers activated the anterior insula, a region associated with negative emotions such as disgust and anger. The stronger the activation, the more likely the player was to reject the offer.

Unfair offers also engaged the dorsolateral prefrontal cortex, which supports deliberate goals such as keeping the money.

So rejection is not a simple error. It can be read as the emotional fairness signal winning out over the cognitive self-interest signal.

Visual Attention

Peshkovskaya et al. (2017) used eye-tracking glasses to study visual perception during the Prisoner’s Dilemma. Total viewing time and fixation time on the non-cooperative option related to each player’s level of cooperation.

Greater attention to the non-cooperative option went with more defection. Where people look predicts how they choose.

Across all these methods, emotion and attention shape strategic choices continuously, and a purely rational model leaves out both.

Critical Evaluation of Game Theory

Game theory gives psychology a precise yardstick, but the people it studies often fail to meet it. Strengths and limitations follow from that gap.

Strengths of Game Theory

Game theory is a rigorous, general language for strategic interdependence. It unites economics, biology, political science, and psychology, and yields precise, testable predictions.

Its greatest gift is a benchmark of pure self-interest. By specifying what a rational egoist would do, game theory turns every human departure into a discovery. Fairness, reciprocity, costly punishment, and default cooperation have all become foundational findings this way (Güth et al., 1982; Fehr & Gächter, 2002).

The simple games also travel well. The same prisoner’s dilemma and ultimatum structures now organize brain-imaging studies of fairness (Sanfey et al., 2003) and multi-society surveys of bargaining norms (Henrich et al., 2001).

The same games work in the scanner, in the field, and in cross-cultural fieldwork. They give researchers a shared experimental currency across laboratories and societies.

Limitations of Game Theory

People break its core assumptions most often. Classical theory assumes rational, self-interested players. Real players are moved by fairness, emotion, trust, and social norms.

Players are also boundedly rational. Simon (1955) argued that decision-makers face limits of information, time, and processing capacity. They usually satisfice: they accept an outcome that is good enough rather than computing the best one.

Predictions are also sensitive to specification. Framing, whether a game is one-shot or repeated, and which equilibrium is selected can all change the result.

It names stable points, but not which one players reach. It also treats payoffs as given, rather than asking where preferences come from.

Behavioral economics, including prospect theory, likewise documents systematic departures from rational choice. Behavioral and evolutionary game theory fill these gaps. They treat fairness and reciprocity as psychological and evolved facts about the players, grafting the missing motives onto the rational-choice skeleton.

Contemporary Research

Modern evidence suggests that fairness and cooperation are defaults of human strategic thinking, not mere exceptions to rationality.

Fairness Across Societies

Henrich et al. (2001) ran standardized bargaining games in 15 small-scale societies. Offers and rejections tracked each community’s market integration and cooperative production. There was no single human constant.

A larger follow-up linked greater market integration and participation in world religions to stronger fairness and punishment (Henrich et al., 2010).

A meta-analysis of ultimatum experiments confirmed systematic cross-cultural variation, especially in responders’ willingness to reject (Oosterbeek et al., 2004).

The pattern is clear. A fairness-and-reciprocity system looks universal, but its settings are shaped by the social world.

Is Cooperation Intuitive?

The social heuristics hypothesis proposes that people carry cooperative habits from everyday life, where interactions repeat and are observed, into the laboratory. Deliberation then nudges them toward self-interest (Rand et al., 2012).

Early studies found that promoting intuition raised cooperation (Rand et al., 2014). A large registered replication found no effect of time pressure specifically (Bouwmeester et al., 2017).

A meta-analysis helps settle the debate.

Because it pools many studies and found no publication bias, this result is more reliable than any single experiment, including the contested replication. The rational actor is not wrong so much as partial: it describes what one deliberative system computes, not what the whole mind does.