Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Observational Learning

Observational Learning

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...

Purposive Learning

Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...

Associative Learning

Associative Learning

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...

Avoidance Learning and Learned Helplessness

Avoidance Learning and Learned Helplessness

Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...

Optimal Foraging

Optimal Foraging

How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.

Reinforcement

Reinforcement

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:

You might also read

Related Articles

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

Sort by

Same author

M phase phosphorylation of the epigenetic regulator UHRF1 regulates its physical association with the deubiquitylase USP7 and stability.

Proceedings of the National Academy of Sciences of the United States of America·2012

Same author

Biosynthesis of ethyl oleate, a primer pheromone, in the honey bee (Apis mellifera L.).

Insect biochemistry and molecular biology·2012

Same author

Co-delivery strategies based on multifunctional nanocarriers for cancer therapy.

Current drug metabolism·2012

Same author

Efficacy of gemifloxacin for the treatment of experimental Staphylococcus aureus keratitis.

Journal of ocular pharmacology and therapeutics : the official journal of the Association for Ocular Pharmacology and Therapeutics·2012

Same author

Expression profile analysis of the polygalacturonase-inhibiting protein genes in rice and their responses to phytohormones and fungal infection.

Plant cell reports·2012

Same author

Characterizing natural dissolved organic matter in a freshly submerged catchment (Three Gorges Dam, China) using UV absorption, fluorescence spectroscopy and PARAFAC.

Water science and technology : a journal of the International Association on Water Pollution Research·2012

Search research articles

Related Experiment Video

Updated: Jan 17, 2026

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

Tailoring knowledge for empowered cooperative actions in multi-agent reinforcement learning.

Hu Fu¹, Yihua Tan¹, Hao Chen²

¹School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Luoyu Road 1037, Wuhan, 430074, Hubei, China.

Neural Networks : the Official Journal of the International Neural Network Society

|September 19, 2025

Summary

This summary is machine-generated.

Tailoring Knowledge for Empowered Cooperative Actions (TKCA) enhances Multi-Agent Reinforcement Learning (MARL) by enabling agents to select specific knowledge, overcoming limitations of partial parameter sharing for better collaboration.

Keywords:

Behavioral diversity Knowledge encoder Knowledge selector Multi-agent reinforcement learning

More Related Videos

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Related Experiment Videos

Last Updated: Jan 17, 2026

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Area of Science:

Artificial Intelligence
Machine Learning
Multi-Agent Systems

Background:

Effective collaboration in Multi-Agent Reinforcement Learning (MARL) relies on behavioral diversity.
Current methods use partial parameter sharing, creating training conflicts and knowledge redundancy due to differing agent needs.
This approach limits scalability and performance in complex MARL scenarios.

Purpose of the Study:

To introduce a novel approach, Tailoring Knowledge for Empowered Cooperative Actions (TKCA), to address limitations in MARL.
To enable agents to acquire and utilize environment-specific knowledge for improved decision-making.
To balance behavioral diversity with algorithmic scalability in cooperative MARL.

Main Methods:

TKCA employs Knowledge Encoders to process diverse environmental knowledge.
A Knowledge Selector network assists individual agents in selecting relevant knowledge for decision-making.
This method facilitates tailored knowledge acquisition for each agent.

Main Results:

TKCA demonstrated superior performance compared to existing methods in challenging StarCraftII micromanagement games.
Evaluations in Google Research Football games also confirmed the effectiveness of the TKCA approach.
The proposed method successfully improved collaborative strategies in complex MARL environments.

Conclusions:

TKCA effectively addresses training conflicts and knowledge redundancy in MARL by tailoring knowledge to individual agents.
The approach enhances agent decision-making and promotes behavioral diversity for improved collaboration.
TKCA offers a promising direction for advancing scalable and high-performing MARL systems.