ALLURE: A Multi-Modal Guided Environment for Helping Children Learn to Solve a Rubik’s Cube with Automatic Solving and Interactive Explanations

Authors

  • Kausik Lakkaraju University of South Carolina
  • Thahimum Hassan University of South Carolina
  • Vedant Khandelwal University of South Carolina
  • Prathamjeet Singh University of South Carolina
  • Cassidy Bradley University of South Carolina
  • Ronak Shah University of South Carolina
  • Forest Agostinelli University of South Carolina
  • Biplav Srivastava University of South Carolina
  • Dezhi Wu University of South Carolina

DOI:

https://doi.org/10.1609/aaai.v36i11.21722

Keywords:

Rubik’s Cube, Education, Reinforcement Learning, AI Explainability, Chatbots, Human Computer Interfaces

Abstract

Modern artificial intelligence (AI) methods have been used to solve problems that many humans struggle to solve. This opens up new opportunities for knowledge discovery and education. We demonstrate ALLURE, an educational AI system for learning to solve the Rubik’s cube that is designed to help students improve their problem solving skills. ALLURE can both find and explain its own strategies for solving the Rubik’s cube as well as build on user-provided strategies. Collaboration between AI and user happens using visual and natural language modalities.
AAAI-22 Proceedings Cover

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Published

2022-06-28

How to Cite

Lakkaraju, K., Hassan, T., Khandelwal, V., Singh, P., Bradley, C., Shah, R., Agostinelli, F., Srivastava, B., & Wu, D. (2022). ALLURE: A Multi-Modal Guided Environment for Helping Children Learn to Solve a Rubik’s Cube with Automatic Solving and Interactive Explanations. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13185-13187. https://doi.org/10.1609/aaai.v36i11.21722

Issue

Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Section

AAAI Demonstration Track