Rock-Paper-Scissors As a Model For Decision-Making

We are often faced with situations where we must compete with others to attain a mutually-exclusive outcome.1 These can be significant, such as seeking a job position amongst numerous other applicants. Or they can be more lighthearted, such as winning a game of poker amongst friends. Game theory is the study of how ‘players’ (such as individuals, companies, and nations) interact and determine strategies in structured competition. Understanding our decision making in these social environments can also help us improve the decisions we make daily.2 

Rock, Paper, Scissors, Shoot!

A typical example of a competitive environment is Rock-Paper-Scissors (RPS) — the simple game where rock crushes scissors, scissors cuts paper, and paper masks rock. Surprisingly, the game’s simplicity has allowed economists to model various aspects of game theory and elucidate our behavior during repeated competition. RPS also enables behavioral economists to compare our assumptions about human rationality with actual behavior.3

Game theory reasonably assumes that the best way to maximize your chances of winning RPS in a repetitive setting is to be unpredictable. In brief, rational behavior in RPS means completely randomizing your choices.4 However, it is quite unfeasible for the human brain to mentally record the frequency of each choice (rock, paper, or scissors) and play randomly (each choice being played precisely 33.33% of the time). This relates to the concept of bounded rationality, which attributes our suboptimal decisions to limitations in time, information, and mental capacity. As a result, the brain instead relies on heuristics — or mental shortcuts — to minimize cognitive load. The most prominent heuristic in RPS is the win-stay lose-shift heuristic.5,6

The win-stay lose-shift heuristic

The win-stay lose-shift heuristic is precisely what it sounds like. This heuristic describes individuals’ tendencies to stick with the same strategy following a win, and switch to different strategy following a draw or loss. For example, if a player chooses rock and wins, they are more likely to play rock again in the next round; if they lose or tie, then they are more likely to play scissors or paper in the next round.5

This heuristic can be explained from an evolutionary perspective. Individuals are more likely to repeat behavior that is positively reinforced and change behavior that is negatively reinforced.5 While such behavior is fundamental, it is somewhat counterintuitive in competitive environments because it increases the predictability of your next move to your opponent. 

Interestingly, one study found that reliance on this heuristic — a deviation from rational decision-making — is more common after losses than wins.3 Looking at how emotion and arousal influence our decision-making can explain this finding. 

The battle between System 1 and System 2 in RPS

System 1 and System 2 are terms coined by psychologists Keith Stanovich and Richard West to model the two types of cognitive processing we have. System 2 describes our ability to think/plan rationally, thoroughly, and strategically. System 1, on the other hand, describes our mind’s intuition and impulsive action that is often driven by emotion and arousal.7

In competitive environments, our success often depends on our ability to keep our System 1 in check and act primarily through our System 2.7 RPS has been used as a way to model the conflict between System 1 and System 2, and with neuroeconomics flourishing as an emerging field of study, recent research has investigated the neural foundations of our decision-making while playing RPS. 

Lewis Forder and Benjamin Dyson, two researchers at the University of Sussex, discovered that following a winning trial, individuals responded with slower reaction times. On the contrary, individuals responded with faster reaction times following a loss/draw trial with a lack of neural activity. Moreover, they found that there was increased neural modulation of brain regions associated with feedback learning following a winning trial in comparison to a losing trial.8 These findings indicate our reliance on System 2 processes following a win System 1 following a loss.


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These findings also explain why the win-stay lose-shift heuristic is more common following a loss — the heuristic violates rational behavior and is likely a result of System 1 thinking.8 This may be due to loss aversion, which describes our tendency to value losses differently than how we value gains. That is to say, we often weigh losses twice as much as gains.9

Practical takeaways

From studies on RPS, we can learn that our ability to remain rational and make sound decisions in competitive situations may be limited to wins. In contrast, following a loss, we tend to make poor decisions, marked by hastiness.

These findings then raise a concern: Are we making sub-par decisions in our daily lives? After all, we encounter losses and high-yield wins every day. Being able to identify such moments can help us recognize times where we may be more prone to making irrational decisions. For example, we may benefit from taking some time before replying to an upsetting email or taking some time after an argument with a family member or colleague before making work/leadership decisions. 

Perhaps, RPS can also teach us something about problem gambling, which is the urge to continue gambling despite incurring losses. While we tend to blame the individuals in cases of problem gambling (the fundamental attribution error), findings from RPS and neuroeconomics suggest that these poor decisions are, in part, due to evolution and out of our immediate control. Following losses while gambling, our reliance on System 1 may cause a failure in our ability to comprehend the risk fully.

These findings may also have applications in individuals predisposed to addiction. Individuals recovering from addiction often fall back into old habits reeling from a loss in another aspect of their life, such as relationships, work, etc. Following such losses, reliance on System 1 may contribute to their vulnerability. Understanding this may improve recovery programs for recovering addicts and problem gamblers. 

In the realm of recreational games like RPS, one study found that professional poker players can control their emotional response to a loss, indicating their ability to make logical decisions continually.10 While we all may not be professionals in managing our emotions to minimize poor decisions, we can all take a first step towards making more logical decisions by recognizing when we may be most vulnerable.

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