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

Reinforcement01:23

Reinforcement

423
Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
423
Reinforcement Schedules01:24

Reinforcement Schedules

261
Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
261
Observational Learning01:12

Observational Learning

372
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...
372
Associative Learning01:27

Associative Learning

654
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
654
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

195
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
195
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

4.5K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
4.5K

You might also read

Related Articles

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

Sort by
Same author

The hub transcription factor ZmbZIP29 controls seed germination speed by promoting starch degradation within the embryo in maize.

Plant communications·2026
Same author

Event-triggered pinning synchronization of stochastic complex networks under hybrid attacks.

Chaos (Woodbury, N.Y.)·2026
Same author

Monte Carlo simulation-based assessment of carcinogenic heavy metal risk following Spartina alterniflora invasion in a subtropical estuarine wetland of China.

Marine pollution bulletin·2026
Same author

Identification of human MLKL Cys184 and HSPBP1 Cys201 as novel cellular targets for necroptosis.

Cell death & disease·2026
Same author

Photocaging the C6-carboxylate of β-glucuronide prodrugs enables spatiotemporally controlled release of anticancer agents <i>via</i> a dual activation strategy.

Organic & biomolecular chemistry·2026
Same author

Industrial Chemical Glycan Synthesis (ICGS): Process Intensification of Glycosylations.

Chem & bio engineering·2026
Same journal

Surface-ligand-triggered synthetic control of defects in nanocrystals toward high-efficiency blue electroluminescence.

Innovation (Cambridge (Mass.))·2026
Same journal

Satellite radar and AIS reveal a 97% decline in shipping traffic through the Strait of Hormuz.

Innovation (Cambridge (Mass.))·2026
Same journal

Hallmarks of health: A Chinese medicine perspective.

Innovation (Cambridge (Mass.))·2026
Same journal

HBV-driven expansion of CXCR6<sup>+</sup>-exhausted T cells and CXCL16<sup>+</sup> macrophage interaction: Implications for immunotherapy in HCC.

Innovation (Cambridge (Mass.))·2026
Same journal

Making the invisible audible: Soft biodegradable implants redefine deep-tissue sensing.

Innovation (Cambridge (Mass.))·2026
Same journal

Dynamic controls on subsurface water chemistry and habitability on icy moons.

Innovation (Cambridge (Mass.))·2026
See all related articles

Related Experiment Video

Updated: Oct 10, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K

DTDE: A new cooperative multi-agent reinforcement learning framework

Guanghui Wen1, Junjie Fu1, Pengcheng Dai1

  • 1Department of Systems Science, School of Mathematics, Southeast University, Nanjing 210096, China.

Innovation (Cambridge (Mass.))
|December 13, 2021
PubMed
Summary

No abstract available in PubMed .

More Related Videos

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

3.1K
A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

701

Related Experiment Videos

Last Updated: Oct 10, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K
RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

3.1K
A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

701