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Related Concept Videos

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...
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Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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...
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...
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Schemata

A schema is a mental construct that organizes related concepts, allowing the brain to process information efficiently. Upon activation, schemata facilitate assumptions about people or objects.
Two types of schemata are:
Schemas01:42

Schemas

A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.

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GODDESS: A Goal-Directed Decision Structuring System.

J Pearl1, A Leal, J Saleh

  • 1SENIOR MEMBER, IEEE, Cognitive Systems Laboratory, School of Engineering and Applied Science, University of California, Los Angeles, CA 90024.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel decision support system (DSS) that uses a goal-directed structure for problem-solving. This computer-aided approach enhances user experience and aids in discovering new action alternatives.

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Area of Science:

  • Decision Analysis
  • Artificial Intelligence
  • Cognitive Science

Background:

  • Traditional decision tree approaches have limitations in representing complex decision problems.
  • Existing decision support systems (DSS) may not fully capture the nuances of human problem-solving.
  • A need exists for more intuitive and comprehensive methods for decision modeling.

Purpose of the Study:

  • To describe an operational, domain-independent computerized decision support system.
  • To introduce a novel, goal-directed structure for representing decision problems.
  • To enhance the validity of user judgments and facilitate the discovery of action alternatives.

Main Methods:

  • Development of a goal-directed structure for decision problem representation.
  • Implementation of a computerized, domain-independent decision support system (DSS).
  • Interaction with users via a stylized English-like dialogue focused on objectives and means.

Main Results:

  • The system allows representation of relations among aspects, effects, conditions, goals, actions, and states.
  • The program focuses user attention on crucial issues during problem-solving.
  • User judgments provide a more valid representation of experience within the system.

Conclusions:

  • The novel goal-directed structure is more compatible with human knowledge encoding.
  • The DSS facilitates the discovery of previously unidentified action alternatives.
  • This approach offers significant advantages over traditional decision-making methods.