Efficient decision heuristics

Warren Thorngate

Systems Research and Behavioral Science · 1980 · 241 citations · 11 references

Concepts

TL;DR

The study investigates how organisms make decisions at the organism level. The authors simulated ten simple decision heuristics as computer subroutines across randomly generated decision scenarios with varying numbers of alternatives and outcomes to assess their selection of highest‑ or lowest‑expected‑value options. The results show that most heuristics, including probability‑ignoring ones, consistently select the highest‑expected‑value alternatives and almost never choose the lowest, supporting motivational explanations over cognitive ones.

Abstract

This article examines decision making in living systems at the level of the organism. Ten simple decision rules, or heuristics, were implemented as computer subroutines in a simulation program designed to determine how often each would select alternatives with highest-through-lowest expected value in a series of randomly generated decision situations. The decision situations varied in their number of alternatives (2, 4, or 8) and outcomes (2, 4, or 8). Results indicated that most of the heuristics, including some which "ignored" probability information, regularly selected alternatives with highest expected value, and almost never selected alternatives with lowest expected value. Implications of this finding for motivational explanations of heuristic use—as opposed to the more popular cognitive explanations—are discussed.

References

11