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Related Concept Videos

Heuristics01:21

Heuristics

Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Reason and Intuition01:37

Reason and Intuition

The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the brain can only use...
Theorems of Pappus and Guldinus: Problem Solving01:12

Theorems of Pappus and Guldinus: Problem Solving

Pappus and Guldinus's theorems are powerful mathematical principles that are used for finding the surface area and volume of composite shapes. For example, consider a cylindrical storage tank with a conical top. Finding the surface area or volume can be challenging for such complex shapes. These theorems are particularly useful in calculating the volume and surface area of such systems. Here, the cylindrical storage tank with a conical top can be broken down into two simple shapes: a cylinder...

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Related Experiment Video

Updated: May 25, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

The wisdom of the crowd in combinatorial problems.

Sheng Kung Michael Yi1, Mark Steyvers, Michael D Lee

  • 1Department of Cognitive Science, University of California, Irvine, CA 92697-5100, USA.

Cognitive Science
|January 25, 2012
PubMed
Summary

The wisdom of the crowd, where group solutions surpass individual ones, extends beyond simple estimates. Aggregated solutions for complex combinatorial problems also outperform individual efforts, broadening its applicability.

Related Experiment Videos

Last Updated: May 25, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Area of Science:

  • Cognitive Science
  • Computational Social Science
  • Decision Science

Background:

  • The "wisdom of the crowd" phenomenon typically applies to problems requiring single numerical estimates.
  • Its applicability to complex problems needing information coordination is less understood.

Purpose of the Study:

  • To investigate if the wisdom of the crowd effect extends to combinatorial problems.
  • To explore aggregation methods for complex problem-solving.

Main Methods:

  • Focus on combinatorial problems: planar Euclidean traveling salesperson, minimum spanning tree, and spanning tree memory task.
  • Development of aggregation methods to combine solution fragments into a global solution.

Main Results:

  • Aggregate solutions, formed by combining common solution fragments, consistently outperformed the majority of individual solutions.
  • Demonstrated the wisdom of the crowd effect in complex combinatorial tasks.

Conclusions:

  • The wisdom of the crowd phenomenon is applicable to problem-solving beyond single numerical estimations.
  • Suggests broader applicability in decision-making scenarios requiring information coordination.