Simple heuristics from the Adaptive Toolbox: Can we perform the requisite learning?

Tim Rakow, Neal Hinvest, Edward Jackson, Martin Palmer

Research output: Contribution to journalArticlepeer-review

18 Citations (SciVal)


The Adaptive Toolbox framework specifies heuristics for choice and categorisation that search through cues in previously learned orders (Gigerenzer & Todd, 1999). We examined the learning of three cue parameters defining different orders: discrimination rate (DR) (the probability that a cue points to a unique choice), validity (the probability of correct choice given that a cue discriminates), and success (the probability of correct choice). Success orderings are identical to those by expected information gain (Klayman & Ha, 1987). In two experiments, participants made choices in real-world environments with objective outcome criteria. Participant ratings indicated some appropriate parameter learning when the relevant cue parameter values were highly dispersed. Rated orders of cue validity and DR were less distinct than the objective orders—learning one parameter may be biased towards success by variation in the other. Success ratings capture the variation in validity and DR as well as participants' perception of these parameters.
Original languageEnglish
Pages (from-to)1-29
Number of pages29
JournalThinking & Reasoning
Issue number1
Publication statusPublished - 2004


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