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

Decision Making01:20

Decision Making

1.3K
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
1.3K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

361
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
361

You might also read

Related Articles

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

Sort by
Same author

Context-Awareness and Biologically Inspired Behaviour Based on Attention Mechanisms for Natural Human-Robot Interaction.

Biomimetics (Basel, Switzerland)·2026
Same author

Bioinspired Stimulus Selection Under Multisensory Overload in Social Robots Using Reinforcement Learning.

Sensors (Basel, Switzerland)·2025
Same author

Creating Expressive Social Robots That Convey Symbolic and Spontaneous Communication.

Sensors (Basel, Switzerland)·2024
Same author

Adaptive Circadian Rhythms for Autonomous and Biologically Inspired Robot Behavior.

Biomimetics (Basel, Switzerland)·2023
Same author

A biologically inspired decision-making system for the autonomous adaptive behavior of social robots.

Complex & intelligent systems·2023
Same author

A Bio-Inspired Endogenous Attention-Based Architecture for a Social Robot.

Sensors (Basel, Switzerland)·2022
Same journal

Multiphysics Investigation on Thermal Characteristics of Internal Bio-Inspired V-Ribbed Cooling Channels for Outer Rotor PMSM.

Biomimetics (Basel, Switzerland)·2026
Same journal

Smart Logistics Model for Supply Chain Management via Brain-Inspired Geometric Deep Networks.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Systematic Taxonomy of the Sunflower Optimization Algorithm: Variants, Hybridization Strategies, Applications, and Research Directions.

Biomimetics (Basel, Switzerland)·2026
Same journal

Toward a Compositional Theory of Trust in Embodied Intelligence: A QNLP Framework for Modeling Context, Interaction, and Trustworthiness.

Biomimetics (Basel, Switzerland)·2026
Same journal

Empirical Logic for Bio-Inspired Soft Computing: Illustrative Applications in Control Engineering and Cluster Analysis.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Modified Multi-Strategy Dhole Optimization Algorithm and Its Engineering Applications.

Biomimetics (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Apr 13, 2026

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.6K

A Bio-Inspired Dopamine Model for Robots with Autonomous Decision-Making.

Marcos Maroto-Gómez1, Javier Burguete-Alventosa1, Sofía Álvarez-Arias1

  • 1Department of Systems Engineering and Automation, University Carlos III of Madrid, Av. de la Universidad, 30, 28911 Leganes, Madrid, Spain.

Biomimetics (Basel, Switzerland)
|August 28, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel dopamine-driven model for autonomous robots, enhancing their adaptive and anticipatory decision-making. The model enables robots to learn optimal strategies and anticipate rewards in dynamic environments.

Keywords:
autonomous behaviourbio-inspirationdopamine modelpleasurereinforcement learningrobotics

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.6K
Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

5.9K

Related Experiment Videos

Last Updated: Apr 13, 2026

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.6K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.6K
Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

5.9K

Area of Science:

  • Robotics
  • Neuroscience
  • Artificial Intelligence

Background:

  • Artificial agents require adaptive decision-making for dynamic environments.
  • Human decision-making is influenced by dopamine, regulating motivation and reward.
  • Emulating human decision-making in robots can improve user interaction.

Purpose of the Study:

  • To propose a computational model of dopamine's role in human motivation and decision-making.
  • To enable autonomous robots to exhibit adaptive and anticipatory behaviors.
  • To integrate the model into a social robot for demonstrating motivated behavior.

Main Methods:

  • Developed a model based on neuroscience findings of dopamine's function.
  • Simulated robot behavior in five distinct environmental scenarios.
  • Integrated the dopamine model into the 'Mini' social robot platform.

Main Results:

  • The model demonstrated effective autonomous behavior and action selection strategies.
  • Dopamine levels were shown to dynamically adjust based on environmental stimuli and robot state.
  • The integrated robot exhibited motivated behavior regulated by biologically inspired internal processes.

Conclusions:

  • The proposed dopamine-driven model successfully enhances robot autonomy and decision-making.
  • The model provides insights into how dopamine influences motivated behavior in artificial agents.
  • This approach offers a pathway for creating more intuitive and understandable human-robot interactions.