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

Conditions on Early Earth02:06

Conditions on Early Earth

101.5K
Around 4 billion years ago, oceans began to condense on earth while volcanic eruptions released nitrogen, carbon dioxide, methane, ammonia, and hydrogen into the primordial atmosphere. However, organisms with the characteristics of life were not initially present on earth. Scientists have used experimentation to determine how organisms evolved that could grow, reproduce, and maintain an internal environment.
101.5K
Classical Conditioning01:18

Classical Conditioning

2.2K
Associative learning, a core principle in behavioral psychology, involves forming connections between events and facilitating learned responses. This concept is vividly illustrated by classical conditioning, a process extensively studied by the Russian physiologist Ivan Pavlov. Pavlov's pioneering research on dogs' digestive systems led to the discovery that behaviors can be learned through association, laying the groundwork for classical conditioning.
Ivan Pavlov observed that dogs...
2.2K
Conditions of Equilibrium01:28

Conditions of Equilibrium

2.1K
Equilibrium refers to a state where a rigid body is not subjected to any translational or rotational motion. This state is achieved when the force and couple acting on a rigid body equal zero. When the system of external forces results in a net effect equivalent to zero, the rigid body is considered to be in equilibrium.
Internal forces are not considered for conditions of equilibrium because they occur in equal and opposite pairs within the body, effectively canceling each other. As a result,...
2.1K
Operant Conditioning01:21

Operant Conditioning

2.9K
Operant conditioning, a key concept in behavioral psychology, involves using reinforcement and punishment to alter the likelihood of a behavior being repeated. B.F. introduced this type of conditioning. Skinner focused on voluntary behaviors and the consequences that follow them, influencing whether these behaviors will be strengthened or diminished.
Reinforcement in operant conditioning can be positive or negative, both of which serve to increase the likelihood of a behavior. Positive...
2.9K
Conditioned Taste Aversion01:14

Conditioned Taste Aversion

607
Conditioned taste aversion, also known as sauce béarnaise syndrome, is a phenomenon in which an individual develops an aversion to a certain food taste following a negative experience, typically illness. This form of aversion is a type of classical conditioning in which the taste of the food (conditioned stimulus, CS) is associated with the experience of illness (unconditioned stimulus, UCS).
A notable characteristic of conditioned taste aversion is that it often requires only a single...
607
Electrostatic Boundary Conditions01:16

Electrostatic Boundary Conditions

966
Consider an external electric field propagating through a homogeneous medium. When the electric field crosses the surface boundary of the medium, it undergoes a discontinuity. The electric field can be resolved into normal and tangential components. The amount by which the field changes at any boundary is given by the difference between the field components above and below the surface boundary.
The surface integral of an electric field is given by Gauss's law in integral form and is related to...
966

You might also read

Related Articles

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

Sort by
Same author

Knowledge Distillation-Based TinyML Model for Breast Cancer Detection Using Real and Wasserstein GAN-Generated Microwave Imaging Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Exploratory Analysis of Concussion Recovery Trajectories using Multi-modal Assessments and Serum Biomarkers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2020
Same author

Examining plant uptake and translocation of emerging contaminants using machine learning: Implications to food security.

The Science of the total environment·2019
Same author

Online Model-Free n-Step HDP With Stability Analysis.

IEEE transactions on neural networks and learning systems·2019
Same author

An Improved N-Step Value Gradient Learning Adaptive Dynamic Programming Algorithm for Online Learning.

IEEE transactions on neural networks and learning systems·2019
Same author

Model Order Reduction Based on Agglomerative Hierarchical Clustering.

IEEE transactions on neural networks and learning systems·2018
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
Same journal

Self-Supervised Continuous Dynamic Graph Representation Learning via Hawkes Processes.

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

cPU: Consistent Risk Estimator for Positive-Unlabeled Learning.

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

Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing.

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

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

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

Related Experiment Video

Updated: Feb 2, 2026

Skeletal Phenotype Analysis of a Conditional Stat3 Deletion Mouse Model
08:42

Skeletal Phenotype Analysis of a Conditional Stat3 Deletion Mouse Model

Published on: July 3, 2020

5.1K

The Boundedness Conditions for Model-Free HDP( λ ).

Seaar Al-Dabooni, Donald Wunsch

    IEEE Transactions on Neural Networks and Learning Systems
    |November 13, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces Heuristic Dynamic Programming with eligibility traces (HDP(λ)), proving its stability and effectiveness. This enhanced approach learns from multiple future rewards, outperforming traditional methods in complex simulations.

    More Related Videos

    A Minimally Invasive Model to Analyze Endochondral Fracture Healing in Mice Under Standardized Biomechanical Conditions
    06:41

    A Minimally Invasive Model to Analyze Endochondral Fracture Healing in Mice Under Standardized Biomechanical Conditions

    Published on: March 22, 2018

    8.6K
    In Vitro and In Vivo Model to Study Bacterial Adhesion to the Vessel Wall Under Flow Conditions
    10:24

    In Vitro and In Vivo Model to Study Bacterial Adhesion to the Vessel Wall Under Flow Conditions

    Published on: June 11, 2015

    11.3K

    Related Experiment Videos

    Last Updated: Feb 2, 2026

    Skeletal Phenotype Analysis of a Conditional Stat3 Deletion Mouse Model
    08:42

    Skeletal Phenotype Analysis of a Conditional Stat3 Deletion Mouse Model

    Published on: July 3, 2020

    5.1K
    A Minimally Invasive Model to Analyze Endochondral Fracture Healing in Mice Under Standardized Biomechanical Conditions
    06:41

    A Minimally Invasive Model to Analyze Endochondral Fracture Healing in Mice Under Standardized Biomechanical Conditions

    Published on: March 22, 2018

    8.6K
    In Vitro and In Vivo Model to Study Bacterial Adhesion to the Vessel Wall Under Flow Conditions
    10:24

    In Vitro and In Vivo Model to Study Bacterial Adhesion to the Vessel Wall Under Flow Conditions

    Published on: June 11, 2015

    11.3K

    Area of Science:

    • Artificial Intelligence
    • Machine Learning
    • Control Theory

    Background:

    • Heuristic Dynamic Programming (HDP) is a model-free approach for reinforcement learning.
    • Eligibility traces are effective in Q-learning but their use in HDP was limited.
    • Previous stability proofs for HDP did not include the λ parameter.

    Purpose of the Study:

    • To analyze the stability of a model-free action-dependent Heuristic Dynamic Programming (HDP) approach with eligibility traces (HDP(λ)).
    • To extend the Uniformly Ultimately Bounded (UUB) proof for HDP to include the λ parameter.
    • To demonstrate the effectiveness of HDP(λ) through simulations.

    Main Methods:

    • Lyapunov stability analysis was used to prove the UUB property of HDP(λ).
    • The stability of critic and actor neural networks, and learning rates was demonstrated.
    • Three case studies involving a nonlinear system, an inverted pendulum, and a 3D maze navigation were conducted.

    Main Results:

    • The Uniformly Ultimately Bounded (UUB) property of HDP(λ) was proven under specific conditions.
    • HDP(λ) demonstrated boundedness of estimated errors for neural networks and learning rates.
    • Simulations showed HDP(λ) achieved competitive performance compared to HDP, TD(λ), and Q(λ) across various scenarios.

    Conclusions:

    • Eligibility traces are beneficial for HDP, enhancing its learning capabilities.
    • HDP(λ) offers a stable and effective reinforcement learning solution.
    • The proposed HDP(λ) method is a valuable contribution for complex control tasks.