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Analyzing Abstraction and Hierarchical Decision-Making in Absolute Identification by Information-Theoretic Bounded
Cecilia Lindig-León1, Sebastian Gottwald1, Daniel A Braun1
1Faculty of Engineering, Computer Science and Psychology, Institute of Neural Information Processing, Ulm University, Ulm, Germany.
Frontiers in Neuroscience
|December 12, 2019
Summary
Human decision-making adapts abstraction levels based on available cognitive resources. This strategy simplifies information processing, optimizing performance under bounded rationality.
Area of Science:
- Cognitive Science
- Decision Theory
- Human Perception
Background:
- Bounded rational decision theory posits that limited cognitive resources necessitate efficient information processing.
- Simplifying information processing involves using generalized actions (abstractions) for similar inputs, saving effort with minimal utility loss.
Purpose of the Study:
- To test the prediction that humans adjust their level of abstraction based on available information-processing resources.
- To investigate how perceptual difficulty and response time influence abstraction level selection in a decision-making hierarchy.
Main Methods:
- Human subjects estimated ellipse roundness, choosing from three precision levels (abstraction levels).
- Information-processing resources were manipulated by varying stimulus identification difficulty and required response times.
Main Results:
- Subjects adapted their chosen level of abstraction in response to changes in available cognitive resources.
- Behavioral data were compared against predictions from a bounded rational decision-making model to assess efficiency.
Conclusions:
- Human decision-making flexibly adjusts abstraction levels to conserve cognitive resources, aligning with bounded rationality principles.
- Understanding these adaptive strategies is key to explaining human efficiency and potential inefficiencies in complex tasks.
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