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Related Experiment Videos

Active learning and decision making: an introduction to the collection.

Jacqueline Gottlieb1, Manuel Lopes2, Pierre-Yves Oudeyer2

  • 1Department of Neuroscience, The Kavli Institute for Brain Science, Columbia University, New York, NY, USA.

F1000Research
|June 23, 2015
PubMed
Summary
This summary is machine-generated.

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This collection explores exploratory behaviors, where agents actively seek information. Understanding these complex actions requires integrating insights from machine learning, neuroscience, and psychology.

Area of Science:

  • Interdisciplinary research
  • Cognitive science
  • Artificial intelligence

Background:

  • Exploratory behaviors are crucial for agents to actively sample information.
  • These behaviors are studied across diverse fields like machine learning, neuroscience, and psychology.
  • Understanding complex exploratory actions necessitates integrating knowledge from multiple disciplines.

Purpose of the Study:

  • To establish a dedicated collection for research on exploratory behaviors.
  • To foster a multidisciplinary approach by including computational, behavioral, and neural studies.
  • To create a valuable resource for researchers investigating information-seeking actions.

Main Methods:

  • The collection accepts various study formats, including full research articles, brief communications, single figure studies, and reviews.

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  • It encompasses diverse methodologies such as computational modeling, behavioral experiments, and neural recordings.
  • This approach allows for a comprehensive examination of exploratory behaviors.

    • Main Results:

    • The collection aims to aggregate a broad spectrum of studies on exploratory behaviors.
    • It serves as a platform for disseminating research employing varied methodologies.
    • The initiative seeks to become a significant resource for the scientific community.

    Conclusions:

    • A multidisciplinary approach is essential for advancing the understanding of exploratory behaviors.
    • This F1000Research collection provides a unified platform for diverse research on the topic.
    • The collection is expected to grow and become a key resource for researchers in the field.