Jove
Visualize
Contact Us

Related Concept Videos

Observational Learning01:12

Observational Learning

528
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
528
Nonconscious Mimicry01:13

Nonconscious Mimicry

4.7K
Nonconscious mimicry occurs when individuals alter their mannerisms to match the behaviors and expressions of those nearby, without intention.
4.7K
Stereotype Content Model02:16

Stereotype Content Model

15.0K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
15.0K
Hierarchy of Motor Control01:18

Hierarchy of Motor Control

4.5K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
4.5K

You might also read

Related Articles

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

Sort by
Same author

Tracklet Pair Proposal and Context Reasoning for Video Scene Graph Generation.

Sensors (Basel, Switzerland)·2021
Same author

Vision-Language-Knowledge Co-Embedding for Visual Commonsense Reasoning.

Sensors (Basel, Switzerland)·2021
Same author

NMN-VD: A Neural Module Network for Visual Dialog.

Sensors (Basel, Switzerland)·2021
Same author

Joint Multimodal Embedding and Backtracking Search in Vision-and-Language Navigation.

Sensors (Basel, Switzerland)·2021
Same author

Spatio-Temporal Action Detection in Untrimmed Videos by Using Multimodal Features and Region Proposals.

Sensors (Basel, Switzerland)·2019
Same author

A Robotic Context Query-Processing Framework Based on Spatio-Temporal Context Ontology.

Sensors (Basel, Switzerland)·2018
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles
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 Experiment Video

Updated: Nov 3, 2025

Investigating Motor Skill Learning Processes with a Robotic Manipulandum
07:52

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

8.9K

Hybrid Imitation Learning Framework for Robotic Manipulation Tasks.

Eunjin Jung1, Incheol Kim1

  • 1Department of Computer Science, Kyonggi University, Suwon-si 16227, Korea.

Sensors (Basel, Switzerland)
|June 2, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a hybrid imitation learning (HIL) framework, combining behavior cloning (BC) and state cloning (SC) for efficient robotic manipulation. HIL significantly improves performance and training speed compared to BC and SC alone.

Keywords:
behavior cloningdynamics modelinghybrid imitation learningrobotic object manipulation tasktrajectory cloning

More Related Videos

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.7K
Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

15.7K

Related Experiment Videos

Last Updated: Nov 3, 2025

Investigating Motor Skill Learning Processes with a Robotic Manipulandum
07:52

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

8.9K
A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.7K
Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

15.7K

Area of Science:

  • Robotics
  • Machine Learning
  • Artificial Intelligence

Background:

  • Robotic manipulation tasks require efficient learning methods.
  • Current imitation learning methods like behavior cloning (BC) and state cloning (SC) have limitations in training efficiency and policy flexibility.
  • Hybrid approaches are being explored to overcome these limitations.

Purpose of the Study:

  • To propose a novel hybrid imitation learning (HIL) framework combining BC and SC for enhanced robotic manipulation task learning.
  • To improve training efficiency and policy flexibility in robotic learning.
  • To demonstrate the effectiveness of the HIL framework through experimental validation.

Main Methods:

  • A hybrid imitation learning (HIL) framework integrating BC and SC.
  • Adaptive loss mixing to combine BC and SC losses.
  • Pretrained dynamics networks to enhance SC efficiency.
  • Stochastic state recovery for stable policy network learning.

Main Results:

  • The HIL framework demonstrated approximately 2.6 times higher performance improvement than pure BC.
  • The HIL framework achieved approximately four times faster training time than pure SC.
  • Compared to BC + Reinforcement Learning (RL), HIL showed 1.6 times higher performance improvement and 2.2 times faster training.

Conclusions:

  • The proposed HIL framework offers significant improvements in training efficiency and policy flexibility for robotic manipulation tasks.
  • HIL provides a superior alternative to pure BC, pure SC, and BC + RL methods.
  • This framework advances the field of imitation learning for complex robotic applications.