User:D.barkoczi/sandbox: Difference between revisions
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:Examples: [[Take-the-best |
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:c) trade-off heuristics |
:c) trade-off heuristics |
Revision as of 14:22, 30 October 2013
An organisms repertoire of specialized cognitive mechanisms including fast and frugal heuristics is referred to as the adaptive toolbox. The basic idea of the adaptive toolbox is that different domains of thought require different specialized tools instead of one universal tool - just as a mechanic can use different specialized tools for different tasks. These specialized tools (heuristics) are effective when they exploit the structure of the information in the environment, that is when they are ecologically rational [1]. They can handle situations of uncertainty involving limited time, computational resources and information. The content of the adaptive toolbox is shaped by evolution, learning, and culture for specific domains of inference and reasoning and changes across the life-span [2].
The adaptive toolbox includes:
1. a specific group of rules or heuristics rather than a general-purpose decision-making algorithm. These heuristics are fast, frugal, and computationally cheap rather than consistent, coherent, and general [1]. Classes and examples of heuristics that are likely to be in the adaptive toolbox of humans and some other animal species include: [1] [3]
- a) recognition-based heuristics:
- Examples: Recognition heuristic , fluency heuristic
- b) one-reason decision-making:
- Examples: Take-the-best, Fast and Frugal Trees
- d) satisficing heuristics
- e) social heuristics:
- Examples: tit for tat, imitate-the-majority, imitate-the-successful, default, social circle heuristic, averaging, plurality vote-based lexicographic heuristics, choosing, group recognition
2. the collection of building blocks (search rules, stopping rules, decision rules) for constructing heuristics,
3. core mental capacities that building blocks exploit (e.g. recognition memory, depth perception, frequency monitoring, object tracking, ability to imitate)
The extent to which humans and other species share heuristics depends on whether they face the same adaptive problems, environments structures, and share core capacities. For example, “while the absence of language production from the adaptive toolbox of other animals means they cannot use name recognition to make inferences about their world, some animal species can use other capacities such as taste and smell recognition as input for the recognition heuristic” (Todd gigerenzer chapter p11).
How are heuristics selected for a given problem?
Alternative views
The concept of the adaptive toolbox departs from the view of that there is a single strategy that is universally superior as put forward by Gottfried Wilhelm Leibniz. “Leibniz [4] dreamed of a universal logical language, the Universal Characteristic, that would replace all reasoning. The multitude of simple concepts constituting Leibniz’s alphabet of human thought were all to be operated on by a single general-purpose tool such as probability theory” [1] Today, a number of approaches exist that assume a universal strategy: for example rational choice theory, the Bayesian approach to cognition [5], parallel constraint satisfaction (PCS) models [6], sequential-sampling process models such as the adaptive spanner perspective [7] and decision field theory [8].
- ^ a b c d Todd, Peter; Gigerenzer, Gerd (2000), "Precis of Simple Heuristics That Make Us Smart", Behavioral and Brain Sciences, 23: 727–780
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instead. - ^ Hertwig, Ralph; Herzog, Stefan (2009), "Fast and Frugal Heuristics: Tools of Social Rationality", Social Cognition, 27: 661–698
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(help) - ^ Leibniz, Gottfried (1995) 'Toward a universal characteristic. In: Leibniz: Selections, Ed: P.P. Wiener. ,Scribner's Sons. ISBN 068412551X ISBN 978-0684125510
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instead. - ^ Glöckner, Andreas; Betsch, Tilmann (2008), "Modeling option and strategy choices with connectionist networks: Towards an integrative model of automatic and deliberate decision making", Judgment and Decision Making, 3: 215–228
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instead. - ^ Busemeyer, Jerome; Townsend, James (1993), "Decision field theory: a dynamic-cognitive approach to decision making in an uncertain environment", Psychological Review, 100: 432–459
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