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Related Concept Videos

Purposive Learning01:22

Purposive Learning

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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...
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Observational Learning01:12

Observational Learning

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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...
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Cognitive Learning01:21

Cognitive Learning

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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...
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Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

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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...
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Associative Learning

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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...
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Introduction to Learning01:18

Introduction to Learning

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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...
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Investigating Motor Skill Learning Processes with a Robotic Manipulandum
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Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition.

Simon Hangl1, Vedran Dunjko2, Hans J Briegel3

  • 1Intelligent and Interactive Systems, Department of Informatics, University of Innsbruck, Innsbruck, Austria.

Frontiers in Robotics and AI
|January 27, 2021
PubMed
Summary
This summary is machine-generated.

Robots learn new manipulation skills through autonomous play, expanding their problem-solving abilities. This approach enhances learning speed and enables robots to tackle previously impossible tasks.

Keywords:
active learningautonomous roboticsbehavior compositionhierarchical modelsreinforcement learningrobotic manipulationskill learning

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Machine Learning

Background:

  • Autonomous robots often have limited manipulation skills for specific situations.
  • Extending these skills to new scenarios is a significant challenge in robotics.

Purpose of the Study:

  • To develop a method for robots to autonomously expand their manipulation skill repertoire.
  • To enable robots to solve previously unsolvable tasks through self-directed learning and environmental interaction.

Main Methods:

  • Robots engage in autonomous play, utilizing existing skills to create situations where known strategies apply.
  • Learned information is used to train an environment model for active learning and generating novel behaviors.
  • The approach is tested on diverse manipulation tasks including grasping, placement, and assembly/disassembly.

Main Results:

  • The proposed method successfully enabled robots to solve previously unsolvable tasks, such as tower disassembly.
  • Composite behavior generation proved effective in expanding the robot's capabilities.
  • Simulations indicated a potential 30% improvement in learning speed through active learning.

Conclusions:

  • Autonomous play is an effective strategy for robots to acquire and generalize manipulation skills.
  • The developed system enhances robotic adaptability and problem-solving in complex manipulation tasks.
  • Active learning significantly accelerates the skill acquisition process in robotic systems.