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Related Concept Videos

Tactile and Chemical Senses01:27

Tactile and Chemical Senses

Tactile senses encompass touch, temperature, and pain, each mediated by specific receptors. Touch receptors detect mechanical energy or pressure against the skin. Sensory fibers from these receptors enter the spinal cord and relay information to the brain stem. Here, most fibers cross over to the opposite side of the brain. The touch information then moves to the thalamus, which projects a map of the body's surface onto the somatosensory areas of the parietal lobes in the cerebral cortex. This...
Purposive Learning01:22

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 bonus...
Piaget's Theory of Cognitive Development from Childhood into Adulthood01:25

Piaget's Theory of Cognitive Development from Childhood into Adulthood

Jean Piaget's theory of cognitive development emphasizes the role of thinking in a child's learning process, suggesting that children are naturally curious about their environment. His approach to development is discontinuous, proposing that cognitive abilities progress through distinct stages, each with unique characteristics. Central to Piaget's theory is schemata—mental structures that allow individuals to understand and interpret the world.
Schemata: Building Blocks of Knowledge
Schemata...
Piaget's Stage 1 of Cognitive Development01:14

Piaget's Stage 1 of Cognitive Development

The sensorimotor stage, the initial phase of Jean Piaget's theory of cognitive development, spans the first two years of a child's life. During this period, infants actively engage with their surroundings, building cognitive awareness through direct interaction with the world. This interaction is primarily based on sensory perception and motor actions, allowing infants to gradually understand basic physical properties and predict how objects interact within their environment.
Exploration...
Sensory Modalities01:15

Sensory Modalities

Sensation typically is the process by which the sensory receptors and sense organs detect stimuli from the internal and external environment and transmit this information to the central nervous system for processing.
General senses refer to the broad category of sensory information detected by receptors in the body and can be further grouped into somatic and visceral senses. Somatic sensations include touch, pressure, temperature, and pain and are essential for navigating our environment and...
Techniques of therapeutic communication I: Active Listening, Sharing Observations, Validation, and Using Touch01:15

Techniques of therapeutic communication I: Active Listening, Sharing Observations, Validation, and Using Touch

The history of therapeutic communication can be traced back to Florence Nightingale, who emphasized the importance of developing trusting relationships with patients. She taught that the presence of nurses with patients results in therapeutic healing.
Therapeutic communication is not the same as social interaction. Social interaction has no goal or purpose and consists of casual information sharing, whereas therapeutic communication has a plan or purpose for the conversation. Therapeutic...

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Related Experiment Video

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Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

Learning tactile skills through curious exploration.

Leo Pape1, Calogero M Oddo, Marco Controzzi

  • 1Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Università della Svizzera Italiana Lugano, Switzerland.

Frontiers in Neurorobotics
|July 28, 2012
PubMed
Summary
This summary is machine-generated.

This study shows how robots can learn tactile exploration skills autonomously using curiosity-driven reinforcement learning. This approach enables robots to develop motor skills and classify textures without explicit programming.

Keywords:
active learningbiomimetic roboticscuriosityintrinsic motivationreinforcement learningskill learningtactile sensing

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Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities
09:38

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities

Published on: January 29, 2014

Related Experiment Videos

Last Updated: May 20, 2026

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities
09:38

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities

Published on: January 29, 2014

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Machine Learning

Background:

  • Robots often require specific algorithms for tactile tasks.
  • Autonomous skill acquisition is challenging for physical robotic systems.

Purpose of the Study:

  • To develop a general curiosity-driven reinforcement learning approach for autonomous tactile skill acquisition.
  • To enable a biomimetic robot finger to learn motor skills and perform texture classification without explicit teacher signals.

Main Methods:

  • Utilized a curiosity-driven reinforcement learning framework on a biomimetic robot finger with microelectromechanical touch sensors.
  • Employed an intrinsic motivation strategy focused on information content and reduced computational resource representation of sensory inputs.

Main Results:

  • The robotic system autonomously developed basic motor skills for tactile exploration from random exploration.
  • The learned motor skills were successfully exploited to solve supervised texture classification tasks.

Conclusions:

  • Demonstrated the feasibility of autonomous tactile skill acquisition on physical robots using curiosity-driven reinforcement learning.
  • Overcame challenges in engineered solutions for active tactile exploration and underactuated control.
  • Provided a foundation for studying developmental learning through intrinsic motivation in robotics.