### abstract ###
the recognition heuristic models the adaptive use and dominant role of recognition knowledge in judgment under uncertainty
of the several predictions that the heuristic makes  empirical tests have predominantly focused on the proposed noncompensatory processing of recognition
some authors have emphasized that the heuristic needs to be scrutinized based on precise tests of the exclusive use of recognition
although precise tests have clear merits  i critically evaluate the value of such tests as they are currently employed
first  i argue that using precise measures of the exclusive use of recognition has to go beyond showing that the recognition heuristic-like every model-cannot capture reality completely
second  i illustrate how precise tests based on response times can lead to unsubstantiated conclusions if the fact that the recognition heuristic does not model the recognition judgment itself is ignored
finally  i highlight two key but so far neglected aspects of the recognition heuristic  a the connection between recognition memory and the recognition heuristic  and b the mechanisms underlying the adaptive use of recognition
### introduction ###
in his essays  the french philosopher michel de montaigne suggested that a good memory is not necessarily coupled with good decision making
in fact  he seems to imply that decisions can sometimes even benefit from deficits in memory
how could this be possible
one answer is that because structures in the mind often reflect meaningful regularities in the world  CITATION   blanks in memory can be exploited for making inferences about the world
the notion that judgments feed on dynamics in memory has been taken up in several models of decision making
for instance  tversky and kahneman  CITATION  proposed that the ease with which instances or occurrences can be brought to mind  is an ecologically valid clue  p  NUMBER  about the world and that an availability heuristic based on this ease might operate when people judge probability or frequency
more recently  goldstein and gigerenzer  CITATION  described the recognition heuristic as a model of how people recruit recognition memory when making inferences more generally
in contrast to the availability heuristic  the recognition heuristic is a clearly specified computational model with precise search  stopping  and decision rules
moreover  the recognition heuristic was proposed as an adaptive mental tool with specific boundary conditions  CITATION
the recognition heuristic makes several testable predictions about recognition and its use in decision making
first  as the recognition heuristic is assumed to be ecologically rational i e   exploiting a regularity in the environment  recognition should be frequently correlated with quantities in the world
second  people's use of the recognition heuristic should be sensitive to the structure of the environment
third  the recognition heuristic predicts that recognition is processed in a noncompensatory fashion-that is  recognition should supersede further cue knowledge
finally  the heuristic predicts  under certain conditions  a counterintuitive less-is-more effect  where recognizing fewer objects can lead to more accurate inferences than recognizing more objects
CITATION the precise definition of the recognition heuristic and its assumed role as an adaptive mental tool made it an attractive study object
maybe not surprisingly  not all empirical investigations have found evidence supporting the heuristic
of the several predictions that the heuristic makes  it seems fair to say that the assumed noncompensatory processing of recognition has received the greatest attention so far-and has generated the strongest objection  CITATION
some authors have emphasized the need for precise tests of the recognition heuristic  and a developed precise measures of the exclusive use of recognition  arguing that  precise models deserve precise measures  and b conducted precise tests of the information processing in recognition-based inference based on response times  CITATION
in the following  i discuss the value of such precise tests as they are currently used and argue that they have done little to advance our understanding of recognition-based inference
in addition  i highlight two key issues underlying the use of recognition in decision making that seem to have been neglected as a result of the strong focus on testing the noncompensatory processing of recognition
first  we need to better understand the relationship between recognition as studied in the memory literature and the recognition memory tapped by the recognition heuristic
second  i summarize proposals of how people might adaptively adjust their reliance on recognition across different situations
importantly  i do not argue that the developments of precise measures or demonstrations of the recognition heuristic's failure to predict data should be ignored
rather  i call for a more constructive way to use these findings for refining models of memory-based decision making
