Towards Software Apprentices that Learn in Dynamic Domains

Abstract

This project made progress on how to create software apprentices, intelligent systems that can operate as collaborators. We did this by developing an account of the representations needed to support flexible learning about dynamic systems, investigating the language understanding and sketch understanding capabilities needed to enable intelligent systems to interact with people as apprentices do, and exploring how to build more autonomous systems, capable of managing their own learning capabilities. This final report describes our progress. We summarize our work on autonomy (including learning via experimentation), natural language, qualitative decision-making, learning from episodic memories, and sketch recognition.

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Document Details

Document Type
Technical Report
Publication Date
Aug 17, 2021
Accession Number
AD1146068

Entities

People

  • Ken Forbus

Organizations

  • Northwestern University

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Economic Systems
  • Formal Languages
  • Instructional Materials
  • Instructors
  • Intelligent Systems
  • Language
  • Natural Languages
  • Production
  • Psychology
  • Reasoning
  • Scientific Research
  • Supervised Machine Learning
  • Thinking

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Theoretical Analysis.

Technology Areas

  • Autonomy