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Related Concept Videos

Decision Making01:20

Decision Making

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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...
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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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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Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
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Reason and Intuition01:37

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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...
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Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

684
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
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Decision Making: P-value Method01:09

Decision Making: P-value Method

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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...
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Quantum Circuit Components for Cognitive Decision-Making.

Dominic Widdows1, Jyoti Rani2, Emmanuel M Pothos3

  • 1IonQ, Inc., 4505 Campus Drive, College Park, MD 20740, USA.

Entropy (Basel, Switzerland)
|May 16, 2023
PubMed
Summary
This summary is machine-generated.

This study shows that quantum computers can successfully run non-classical human decision-making models. Quantum cognitive models, using principles like superposition, offer new ways to understand cognitive behaviors that defy classical probability.

Keywords:
cognitive decision-makingquantum cognitionquantum computing

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Area of Science:

  • Cognitive Science
  • Quantum Computing
  • Computational Neuroscience

Background:

  • Human decision-making often violates classical probability and set theory.
  • Quantum probability, using subspace projections, successfully models phenomena like order effects in surveys.
  • Quantum computing hardware is now advanced enough for cognitive modeling.

Purpose of the Study:

  • To demonstrate the feasibility of running non-classical cognitive models on quantum computers.
  • To develop quantum circuit representations for quantum cognitive models.
  • To explore quantum computing for modeling decision-making under uncertainty and order effects.

Main Methods:

  • Representing mental states using qubit registers.
  • Implementing cognitive operations and decisions with quantum gates and measurements.
  • Developing quantum circuit representations for quantum cognitive models.

Main Results:

  • Successful implementation of non-classical cognitive models as quantum circuits.
  • Demonstration of quantum circuit representations for order effects and decision-making under uncertainty.
  • Validation of quantum probability's applicability to cognitive phenomena.

Conclusions:

  • Quantum computers offer a viable platform for investigating quantum cognitive models.
  • The mathematics of quantum cognition and quantum computing provide a shared language for modeling.
  • Quantum properties like superposition and entanglement are key to this interdisciplinary approach.