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Developing Hierarchical Schemas and Building Schema Chains Through Practice Play Behavior.

Suresh Kumar1,2, Patricia Shaw1, Alexandros Giagkos1

  • 1Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom.

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Summary
This summary is machine-generated.

This study introduces Dev-PSchema, a system that enables artificial agents to learn complex tasks through playful interaction and schema generation. The system simulates infant learning preferences, advancing developmental robotics and AI.

Keywords:
Dev-PSchemaaction sequencingmodeling of behaviorplay and playthingspractice playschema chainsschemas

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Area of Science:

  • Developmental psychology
  • Robotics
  • Artificial Intelligence

Background:

  • Human infants learn through distinct stages of play: practice, symbolic, and rule-based.
  • Practice play allows infants to build knowledge schemas from sensorimotor experiences with objects.
  • Schemas can be combined hierarchically to form complex, multi-step behaviors.

Purpose of the Study:

  • To present Dev-PSchema, a schema-based play generator for artificial agents.
  • To demonstrate the system's ability to learn sensorimotor schemas from playful interaction.
  • To showcase the autonomous execution of complex tasks via schema chaining.

Main Methods:

  • Development of the Dev-PSchema system for artificial agents.
  • Experiments conducted in a simulated environment.
  • Testing with the iCub robot for real-world validation.

Main Results:

  • Dev-PSchema successfully creates schemas from playful interaction.
  • The system generates schema chains enabling autonomous complex task performance.
  • Dev-PSchema simulates diverse infant learning preferences for novel versus familiar objects.

Conclusions:

  • Playful interaction is a viable mechanism for artificial agents to acquire complex skills.
  • Schema chaining provides a hierarchical structure for autonomous behavior generation.
  • The system's ability to model learning preferences enhances developmental robotics research.