The Mnemonic Decision Maker : How Search in Memory Shapes Decision Making
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The starting point of the dissertation was the question how people search for information in memory when they make decisions. Following the perspective of ecological rationality (e.g., Gigerenzer et al., 1999), successful decision strategies are anchored both in the human mind and in the environment. Adaptive decision making thus requires that people adapt their strategies both to the structure of the environment and to the limitations of the cognitive system. In this regard, I am sympathetic to the view put forward for example by Schooler and Hertwig (2005) that these limitations may be functional. Among other functions, they shape how people search for information in memory by facilitating certain ways of searching for information, but hindering others.
In Chapter 1, I have explored the counterintuitive finding that people with a lower short-term memory capacity outperform people with a higher short-term memory capacity in a correlation detection task (Kareev et al., 1997), which is highly similar to classic binary choice probability learning tasks. It turned out that the success of people with lower capacities lies in the simplicity of their strategy. In contrast, people with higher capacities explored too much and looked for patterns in the sequence of events and ended up with behavior that looked like probability matching. Since there were no patterns, this more exploratory behavior was counterproductive in this task. It helped, however, to detect changes in the environment. It could very well be that the process underlying probability matching, searching for patterns, is usually smart, because often the cost of missing a non-random sequence could well be higher than the price of detecting patterns where there are none (Lopes, 1982). But it looks stupid in stationary binary choice tasks with conditions that rarely hold outside of psychological laboratories and casinos (Ayton & Fischer, 2004). Probability matching, or its underlying process, could thus smarter than it appears at first glance.
Many decisions we have to face, however, will neither be as simple as the binary choice paradigm nor depend on such a dearth of information. Therefore, Chapter 2 dealt with memory-based decisions in a more complex environment with several cues. When probabilistic inferences have to be made from cue values stored in long-term memory, many participants appear to use fast and frugal heuristics, such as “take-the best” (TTB), that assume sequential search of cues (Bröder & Schiffer, 2003b, 2006). A simultaneous global matching process with cue weights that are appropriately chosen would mimic the decision outcomes, albeit assuming different cognitive processes. A reanalysis of response times (RTs) from five published experiments (n = 415) and one new experiment (n = 82) is presented that support the assumption of sequential search. In all instances in which decision outcomes indicated the use of TTB’s decision rule, decision times increased monotonically with the number of cues that had to be searched in memory. Furthermore, RT patterns fitted the outcome-based strategy classifications, which further validates both measures.
Simple cue-based heuristics such as TTB owe much of their success to a correct order in which cues are considered (here: by cue validity). This prerequisite of TTB makes it a more difficult strategy than it appears to be at first glance (Juslin & Persson, 2002). In Chapter 3, I therefore explored whether there would be a simpler but still successful way people could go about ordering the cues, namely by simply ordering them by the speed with which they retrieve them from memory. The results supported the idea that people do not need to know how important different cues are to order them successfully. They can let the environment do the work and rely on how the environment is reflected in their memory by simply considering cues in the order with which they are retrieved.
More generally, the dissertation has contributed to show that humans do neither need complete information nor unlimited time to make good judgments. The strategies they use are well adapted both to the environment and to the human mind and can thus be successful and simple at the same time. The memory system can help by shaping the way people search for information they have stored. It can guide the search towards useful information and can prevent people from searching too much information, which could be unnecessary or even detrimental.
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GAISSMAIER, Wolfgang, 2007. The Mnemonic Decision Maker : How Search in Memory Shapes Decision MakingBibTex
@book{Gaissmaier2007Mnemo-27922, year={2007}, title={The Mnemonic Decision Maker : How Search in Memory Shapes Decision Making}, author={Gaissmaier, Wolfgang}, note={http://nbn-resolving.de/urn:nbn:de:kobv:188-fudissthesis000000005913-2***Berlin, Freie Universität Berlin, Diss., 2007} }
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Following the perspective of ecological rationality (e.g., Gigerenzer et al., 1999), successful decision strategies are anchored both in the human mind and in the environment. Adaptive decision making thus requires that people adapt their strategies both to the structure of the environment and to the limitations of the cognitive system. In this regard, I am sympathetic to the view put forward for example by Schooler and Hertwig (2005) that these limitations may be functional. Among other functions, they shape how people search for information in memory by facilitating certain ways of searching for information, but hindering others.<br />In Chapter 1, I have explored the counterintuitive finding that people with a lower short-term memory capacity outperform people with a higher short-term memory capacity in a correlation detection task (Kareev et al., 1997), which is highly similar to classic binary choice probability learning tasks. It turned out that the success of people with lower capacities lies in the simplicity of their strategy. In contrast, people with higher capacities explored too much and looked for patterns in the sequence of events and ended up with behavior that looked like probability matching. Since there were no patterns, this more exploratory behavior was counterproductive in this task. It helped, however, to detect changes in the environment. It could very well be that the process underlying probability matching, searching for patterns, is usually smart, because often the cost of missing a non-random sequence could well be higher than the price of detecting patterns where there are none (Lopes, 1982). But it looks stupid in stationary binary choice tasks with conditions that rarely hold outside of psychological laboratories and casinos (Ayton & Fischer, 2004). Probability matching, or its underlying process, could thus smarter than it appears at first glance.<br /><br /><br />Many decisions we have to face, however, will neither be as simple as the binary choice paradigm nor depend on such a dearth of information. Therefore, Chapter 2 dealt with memory-based decisions in a more complex environment with several cues. When probabilistic inferences have to be made from cue values stored in long-term memory, many participants appear to use fast and frugal heuristics, such as “take-the best” (TTB), that assume sequential search of cues (Bröder & Schiffer, 2003b, 2006). A simultaneous global matching process with cue weights that are appropriately chosen would mimic the decision outcomes, albeit assuming different cognitive processes. A reanalysis of response times (RTs) from five published experiments (n = 415) and one new experiment (n = 82) is presented that support the assumption of sequential search. In all instances in which decision outcomes indicated the use of TTB’s decision rule, decision times increased monotonically with the number of cues that had to be searched in memory. Furthermore, RT patterns fitted the outcome-based strategy classifications, which further validates both measures.<br /><br /><br />Simple cue-based heuristics such as TTB owe much of their success to a correct order in which cues are considered (here: by cue validity). This prerequisite of TTB makes it a more difficult strategy than it appears to be at first glance (Juslin & Persson, 2002). In Chapter 3, I therefore explored whether there would be a simpler but still successful way people could go about ordering the cues, namely by simply ordering them by the speed with which they retrieve them from memory. The results supported the idea that people do not need to know how important different cues are to order them successfully. They can let the environment do the work and rely on how the environment is reflected in their memory by simply considering cues in the order with which they are retrieved.<br /><br /><br />More generally, the dissertation has contributed to show that humans do neither need complete information nor unlimited time to make good judgments. The strategies they use are well adapted both to the environment and to the human mind and can thus be successful and simple at the same time. The memory system can help by shaping the way people search for information they have stored. It can guide the search towards useful information and can prevent people from searching too much information, which could be unnecessary or even detrimental.</dcterms:abstract> <dc:contributor>Gaissmaier, Wolfgang</dc:contributor> <dcterms:title>The Mnemonic Decision Maker : How Search in Memory Shapes Decision Making</dcterms:title> <dcterms:alternative>Der mnemonische Entscheider : Wie die Suche im Gedächtnis unsere Entscheidungen formt</dcterms:alternative> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> </rdf:Description> </rdf:RDF>