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Related Concept Videos

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...
Perception01:28

Perception

Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
Bottom-up processing begins at the sensory level, where receptors detect external environmental stimuli. These could include the tactile sensation of...
Cognitive Learning01:21

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Observational Learning01:12

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 because...
Introduction to Learning01:18

Introduction to Learning

Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
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
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Related Experiment Video

Updated: May 12, 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

Learning and exploration in action-perception loops.

Daniel Y Little1, Friedrich T Sommer

  • 1Department of Molecular and Cell Biology, Redwood Center for Theoretical Neuroscience, University of California Berkeley, CA, USA.

Frontiers in Neural Circuits
|April 13, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new exploration strategy for machine learning agents, prioritizing learning an accurate internal model over external rewards. This approach enhances learning efficiency and task performance, offering insights into biological exploration.

Keywords:
behavioral psychologycomputational neurosciencecontrol theoryinformation theoryknowledge acquisitionmachine learning

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Area of Science:

  • Machine Learning
  • Neuroscience
  • Cognitive Science
  • Computational Biology

Background:

  • Discovering data structure is key in machine learning and brain function.
  • Behavior significantly impacts learning efficiency in action-perception loops.
  • Existing models prioritize reward maximization over learning data structure.

Purpose of the Study:

  • Investigate learning-driven behavior without external rewards.
  • Prioritize the quality of an agent's internal model.
  • Develop and evaluate novel exploration strategies.

Main Methods:

  • Derived a Bayesian estimate for expected information gain (PIG) per action.
  • Developed exploration strategies to maximize PIG.
  • Utilized value-iteration for an efficient exploration strategy.

Main Results:

  • The PIG-maximizing strategy learns faster than prior reward-free methods.
  • Agents with efficient exploration exhibit better performance on later tasks.
  • Demonstrated the utility of accurate internal models for goal-directed behavior.

Conclusions:

  • Learning-driven exploration, focused on internal model accuracy, is a viable and effective objective.
  • This framework explains animal and human exploratory behaviors.
  • Potential applications in experimental design, including closed-loop neurophysiology.