- Ecological Rationality: Intelligence in the World - Oxford Scholarship
- Gerd Gigerenzer
- Ecological Rationality: Intelligence in the World
- Demons of Ecological Rationality
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In he moved to the University of Konstanz and in to the University of Salzburg.carmepujol.eu/templates/bridge/gige-sexo-gratis.php
Ecological Rationality: Intelligence in the World - Oxford Scholarship
Gigerenzer was awarded honorary doctorates from the University of Basel and the Open University of the Netherlands. With Daniel Goldstein he first theorized the recognition heuristic and the take-the-best heuristic. They proved analytically conditions under which semi-ignorance lack of recognition can lead to better inferences than with more knowledge. These results were experimentally confirmed in many experiments, e. Similarly, decisions by experienced experts e. A third class of heuristics, Fast-And-Frugal trees , are designed for categorization and are used for instance in emergency units to predict heart attacks, and model bail decisions made by magistrates in London courts.
In such cases, the risks are not knowable and professionals hence face uncertainty. To better understand the logic of Fast-And-Frugal trees and other heuristics, Gigerenzer and his colleagues use the strategy of mapping its concepts onto those of well-understood optimization theories, such as signal-detection theory. A critic of the work of Daniel Kahneman and Amos Tversky , Gigerenzer argues that heuristics should not lead us to conceive of human thinking as riddled with irrational cognitive biases, but rather to conceive rationality as an adaptive tool that is not identical to the rules of formal logic or the probability calculus.
He and his collaborators have theoretically and experimentally shown that many cognitive fallacies are better understood as adaptive responses to a world of uncertainty—such as the conjunction fallacy , the base rate fallacy , and overconfidence. The basic idea of the adaptive toolbox is that different domains of thought require different specialized cognitive mechanisms instead of one universal strategy. The analysis of the adaptive toolbox and its evolution is descriptive research with the goal of specifying the core cognitive capacities such as recognition memory and the heuristics that exploit these such as the recognition heuristic.
Alongside his research on heuristics, Gigerenzer investigates risk communication in situations where risks can actually be calculated or precisely estimated. He has developed an ecological approach to risk communication where the key is the match between cognition and the presentation of the information in the environment.
For instance, lay people as well as professionals often have problems making Bayesian inferences , typically committing what has been called the base-rate fallacy in the cognitive illusions literature. Gigerenzer and Ulrich Hoffrage were the first to develop and test a representation called natural frequencies , which helps people make Bayesian inferences correctly without any outside help. Later it was shown that with this method, even 4th graders were able to make correct inferences. Once again, the problem is not simply in the human mind, but in the representation of the information.
Gigerenzer has taught risk literacy to some 1, doctors in their CMU and some 50 US federal judges, and natural frequencies has now entered the vocabulary of evidence-based medicine. In recent years, medical schools around the world have begun to teach tools such as natural frequencies to help young doctors understand test results. An upperbound on the number of heuristics and the size of a heuristic.
A lowerbound for the level of adaptation that counts as ecologically rational. Output: A toolbox , of bounded size, that is ecologically rational. A fast and frugal tree is a chain of cues with associated actions in case of a heuristic or a chain of cues with associated heuristics in case of the selector. Each cue is a boolean function, evaluating whether an event is true in a given situation. If the cue evaluates to true, then the heuristic associated with that selector cue is used in case of the selector or an action associated with that heuristic cue is executed in case of a heuristic.
If the cue is false, the next cue is evaluated until the last cue is reached. If this last cue is false, the first heuristic is used in case of the selector or the last action in the tree is performed in case of a heuristic.
For instance, this process could be an ontogenetic or phylogenetic process, or a mixture of these. Furthermore, it does not make specific assumptions about how these processes are realized, for example, algorithmically. The reason is that computational intractability i. Show that after the transformed input is processed as specified by Toolbox Adaptation, the resulting output o AT can be transformed back into a solution o DS for Dominating Set proof steps 2 and 3.
Both transformations only take polynomial time to compute. This means we can use Toolbox Adaptation to solve Dominating Set with minimal only polynomial overhead. It is assumed that the class BPP is equal to P, so that functions which can be solved probabilistically in polynomial time can also be solved deterministically in polynomial time Wigderson,.
This applies regardless of the nature of this process. This is an interesting observation given that one of the prime motivations for the Adaptive Toolbox theory was to move away from classical notions of rationality, based on logic or probability, in order to ensure tractability. Our proof that Toolbox Adaptation is intractable may be surprising, given that it is so widely believed that the Adaptive Toolbox theory is a tractable account of human rationality.
Ecological Rationality: Intelligence in the World
We suspect that the belief could persist, however, because researchers have been focusing on Toolbox Application , while taking Toolbox Adaptation for granted. Here, Toolbox Application refers to the process of making ecologically rational decisions in a given environment, using a toolbox of heuristics that has already been adapted to that environment by some unspecified process. Even if Toolbox Application is free from computational demons, the demons are still hiding in Toolbox Adaptation. It is not uncommon for cognitive scientists to try to discredit theories in competing frameworks by pointing out that those frameworks run into intractability issues.
But this is to no avail and is in no way our purpose here. We see intractability not as a problem for specific theories, or even for specific theoretical frameworks, but a ubiquitous feature of theoretical frameworks with high degrees of generality van Rooij, , By overlooking the question how adaptation of toolboxes of heuristics can itself be tractable, Gigerenzer and colleagues may not have realized that the Adaptive Toolbox theory faces exactly the same intractability charge, albeit in a different guise.
Demons of Ecological Rationality
Does this mean that the Adaptive Toolbox account is irreparably flawed? Certainly not.
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The model can then potentially be rendered tractable by assuming that the relevant parameters are, in the real world, bounded in the right ways. In other words, these bounds limit the degrees of freedom of the theory so that it becomes tractable for ecologically relevant parameter ranges.
For instance, one may intuitively conjecture that Toolbox Adaptation is tractable for toolboxes of bounded size e.