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

Observational Learning01:12

Observational Learning

126
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...
126
Language Development01:22

Language Development

314
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
314
Stereotype Content Model02:16

Stereotype Content Model

14.0K
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...
14.0K
Language01:16

Language

190
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
190
What is Behavior?00:54

What is Behavior?

8.9K
Behaviors are actions that an organism engages in—they can be related to finding food, reproducing, defending against threats, and many other possible actions. Behaviors include activities related to the environment around the animal—such as migration—as well as social interactions within a species or population. Many behaviors involve motor output—that is, muscle movements—while others involve less visible actions, such as learning.
8.9K
Concepts and Prototypes01:24

Concepts and Prototypes

90
The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
90

You might also read

Related Articles

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

Sort by
Same authorSame journal

Learning flight navigation like a honey bee.

Science robotics·2026
Same author

Fusing LiDAR and vision to generate high-quality reconstructions.

Science robotics·2026
Same author

Dexterous grasping with an active palm.

Science robotics·2026
Same author

Vibrotactile feedback aids prosthesis usability.

Science robotics·2026
Same author

Collision-tolerant deformable quadrotor arms.

Science robotics·2026
Same author

A self-guided intubation device.

Science robotics·2026

Related Experiment Video

Updated: May 31, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

484

Humanoid robot learning of complex behaviors with LLMs.

Amos Matsiko1

  • 1Science Robotics, AAAS, Washington, DC 20005, USA.

Science Robotics
|January 22, 2025
PubMed
Summary

Large language models can help humanoid robots learn complex behaviors through natural interactions. This approach enhances robot learning and adaptability for real-world tasks.

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Human-Robot Interaction

Background:

  • Humanoid robots require sophisticated methods for learning complex behaviors.
  • Traditional robot learning methods often lack natural interaction capabilities.
  • Large Language Models (LLMs) offer advanced natural language understanding and generation.

Purpose of the Study:

  • To investigate the efficacy of LLM-assisted natural interactions for humanoid robot learning.
  • To explore how LLMs can facilitate the acquisition of complex behaviors in robots.
  • To enhance the adaptability and versatility of humanoid robots through AI-driven interaction.

Main Methods:

  • Utilizing large language models to process and generate natural language instructions.
  • Developing interaction protocols for seamless communication between humans and humanoid robots.

More Related Videos

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.4K
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

8.7K

Related Experiment Videos

Last Updated: May 31, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

484
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.4K
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

8.7K
  • Implementing machine learning algorithms for behavior acquisition based on LLM-mediated input.

    • Main Results:

    • Humanoid robots demonstrated accelerated learning of complex tasks when aided by LLMs.
    • Natural interactions facilitated by LLMs led to more intuitive and efficient robot behavior acquisition.
    • The proposed method showed significant improvements in robot adaptability to novel situations.

    Conclusions:

    • Large language models are a promising tool for enabling natural interaction-based learning in humanoid robots.
    • LLM-assisted learning can significantly advance the capabilities of humanoid robots for complex tasks.
    • This research paves the way for more intuitive and effective human-robot collaboration.