Satisficing, explained.
Satisficing chooses an option that meets an aspiration level rather than exhaustively finding the best possible option.
Why it happens
Twelve seeded integer offers lie between 0 and 100. Each inspection costs two units, and past offers expire. Set an aspiration level, inspect sequentially and accept the current offer. Net payoff equals its value minus accumulated inspection costs.
Satisficing chooses an option that meets an aspiration level rather than exhaustively finding the best possible option.
Read the result
Track the cost of each inspection alongside the offer. A higher discovered offer can still produce a lower net payoff after extra search.
A worked example
A good-enough tool under search costs
Set an aspiration level of seventy and pay two units to inspect the first offer, noting whether it meets the threshold.
Continue or accept; each new offer replaces the previous opportunity and adds another two units of search cost.
After accepting, compare value with accumulated cost. The unseen maximum is not the same as the best achievable net decision under limited information.
OPTIONAL DEEPER DETAILGo deeper: inside the model
Inside this model
Twelve seeded integer offers lie between 0 and 100. Each inspection costs two units, and past offers expire. Set an aspiration level, inspect sequentially and accept the current offer. Net payoff equals its value minus accumulated inspection costs.
Where this idea is useful
A practical use
A person comparing routine tools can set minimum requirements and a search budget instead of spending indefinitely on marginal improvements.
A common misconception
“Satisficing means choosing carelessly or accepting anything.”
An aspiration rule can encode explicit requirements and respect search costs. Its quality depends on how the requirements fit the actual decision.
What this explanation leaves out
- The aspiration threshold is a heuristic, not a solved optimal stopping policy. The distribution and inspection costs are fictional; the game omits multidimensional quality and changing requirements.
Is seventy the optimal threshold here?
The interface does not solve an optimal stopping problem. Seventy is a starting aspiration you can question, not a recommendation derived from the offer distribution.
What minimum requirements and search budget would make a current low-stakes decision easier to finish?
Associated thinkers
Associations marked provisional are awaiting source review.
Further reading
Explore the original research or the teaching reference behind this experiment.