Rationality for Mortals: How People Cope with Uncertainty

By Gerd Gigerenzer. 2008

452 citations recorded by the source corpus.

Subfields: General Decision Sciences, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/84ec357e508083de01c259b8075fed70ee89b8de

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In General Decision Sciences

In Management Science and Operations Research

Citations in the corpus

Computational rationality: A converging paradigm for intelligence in brains, minds, and machines (2015, background): “In the 1970s and 1980s, this hypothesis met with resistance from researchers who uncovered systematic fallacies in probabilistic reasoning and decision-making (24), leading some to adopt models based on informal heuristics and biases rather than normative principles of probability and utility theory”
Toward a Rational and Mechanistic Account of Mental Effort. (2017, background): “Theories of bounded rationality (Gigerenzer 2008; Simon 1956, 1982; Todd & Gigerenzer 2012) attribute these suboptimalities to people’s reliance on simplifying heuristics in lieu of more exhaustive deliberation.”
Girls get smart, boys get smug: Historical changes in gender differences in math, literacy, and academic social comparison and achievement (2017, background): “…for humans to act as pure rational agents but nevertheless increases the complexity of relevant models) is that individuals act according to bounded rationality (Simon, 1972) or operate according to what Gigerenzer (2008) calls rationality for mortals (i.e., allow for cognitive shortcuts).”
Heuristic decision making. (2011, unknown): “This " bias-variance dilemma " helps to explicate the rationality of simple heuristics and how less can be more (Brighton & Gigerenzer 2008, Gigerenzer & Brighton 2009).”
The effect of anger and anxiety traits on investment decisions (2012, result): “Research in this field is in fact primarily experimental and there is a general disagreement about the level of external validity of the results because this kind of studies tested participants in artificial conditions that bear little resemblance to the outside world (e.g., Gigerenzer, 2008).”
Troubles with Bayesianism: An introduction to the psychological immune system (2018, background): “For one thing, they have been known for some time (see, e.g., Gigerenzer, 2008); for another, figuring out the actual psychological implementation (i.e., the algorithmic-level explanation) for Bayesian reasoning is an active research program, one which many clever theorists are currently engaged in.”
One and Done? Optimal Decisions From Very Few Samples (2014, background): “Another related argument comes from proponents of “bounded rationality” (Gigerenzer, 2008; Simon, 1956): Given cognitive limitations, strict optimization is impractical if not impossible, and instead people may adopt heuristics that are sufficient for good performance.”
The meaning of risk-taking – key concepts and dimensions (2019, background): “…to improve people’s engagement with risk is generating a growing body of approaches which, for example, provide risk knowledge in an accessible way (Gigerenzer 2010; Fischhoff and Kadvany 2011), influence the choice architecture of people’s environment (Thaler and Sunstein 2009), change behaviour…”