Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Decision Making01:20

Decision Making

994
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...
994
Fixed Action Patterns01:06

Fixed Action Patterns

17.7K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
17.7K
Decision Making: P-value Method01:09

Decision Making: P-value Method

7.0K
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...
7.0K
Action Potentials01:41

Action Potentials

142.8K
Overview
142.8K
Action Potential01:31

Action Potential

4.7K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
4.7K
Action Potential01:14

Action Potential

11.4K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they receive...
11.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Synthesis and herbicidal activity of optically active α-(substituted phenoxyacetoxy) (substituted phenyl) methylphosphonates.

Pesticide biochemistry and physiology·2017
Same author

S149R, a novel mutation in the <i>ABCD1</i> gene causing X-linked adrenoleukodystrophy.

Oncotarget·2017
Same author

Transgenic cotton co-expressing chimeric Vip3AcAa and Cry1Ac confers effective protection against Cry1Ac-resistant cotton bollworm.

Transgenic research·2017
Same author

Effective adsorption of nitroaromatics at the low concentration by a newly synthesized hypercrosslinked resin.

Water science and technology : a journal of the International Association on Water Pollution Research·2017
Same author

Comparative Genome Analysis Reveals Adaptation to the Ectophytic Lifestyle of Sooty Blotch and Flyspeck Fungi.

Genome biology and evolution·2017
Same author

Highly Efficient Separation of Trivalent Minor Actinides by a Layered Metal Sulfide (KInSn<sub>2</sub>S<sub>6</sub>) from Acidic Radioactive Waste.

Journal of the American Chemical Society·2017
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026
Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026
Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Feb 7, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

1.1K

Hierarchical Decision and Control for Continuous Multitarget Problem: Policy Evaluation With Action Delay.

Jiangcheng Zhu, Jun Zhu, Zhepei Wang

    IEEE Transactions on Neural Networks and Learning Systems
    |July 12, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel autonomous control algorithm for aerial robots in the shepherd game. The approach enables robots to intelligently manage action delays for optimal performance in time-sensitive missions.

    More Related Videos

    An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
    07:42

    An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents

    Published on: August 2, 2018

    14.4K
    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.4K

    Related Experiment Videos

    Last Updated: Feb 7, 2026

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
    06:04

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

    Published on: February 14, 2025

    1.1K
    An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
    07:42

    An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents

    Published on: August 2, 2018

    14.4K
    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.4K

    Area of Science:

    • Robotics
    • Artificial Intelligence
    • Control Systems

    Background:

    • The International Aerial Robotics Competition (IARC) shepherd game requires autonomous aerial robots to herd ground vehicles.
    • Existing control algorithms struggle with non-constant action delays that depend on task rewards.
    • Developing a time-aware decision-making process is crucial for autonomous aerial robot performance.

    Purpose of the Study:

    • To propose a hierarchical decision-making and control algorithm for autonomous aerial robots in the IARC shepherd game.
    • To address the challenge of non-constant action delays by making the agent "aware of time" during action execution.
    • To improve the efficiency and effectiveness of aerial robot control in time-critical, autonomous missions.

    Main Methods:

    • Developed a hierarchical decision-making and control algorithm for multirotor aerial robots.
    • Implemented deep Q-networks and a lookup table to manage time-dependent action delays.
    • Utilized a lower-level controller to fit an action delay predictor at the decision-making level.

    Main Results:

    • Validated the effectiveness and efficiency of the proposed algorithm through simulations of the shepherd game.
    • The algorithm enabled the aerial robot agent to successfully contact and herd ground targets within the time limit.
    • Achieved first prize in the IARC 2017 competition and maintained the mission's best record.

    Conclusions:

    • The proposed hierarchical algorithm successfully addresses the challenge of non-constant action delays in autonomous aerial robot control.
    • The "time-aware" decision-making approach enhances robot performance in time-sensitive tasks like the shepherd game.
    • This research demonstrates a significant advancement in autonomous robotics for complex, real-world missions.