Learning and Playing in Wubble World

Authors

  • Wesley Kerr University of Southern California
  • Paul Cohen University of Southern California
  • Yu-Han Chang University of Southern California

DOI:

https://doi.org/10.1609/aiide.v4i1.18674

Abstract

Children do not learn the meanings of words from parsing and understanding gigabytes of text; instead meanings are learned from competent speakers who relate language to what's happening in the child's environment. We present a word learning algorithm that operates in a video game environment where the players fill the role of the competent speakers and train softbots to learn language as a child would. We provide empirical evidence that the word learning algorithm successfully learns the meanings for some words in this environment and the children enjoy playing the game.

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Published

2021-09-27

How to Cite

Kerr, W., Cohen, P., & Chang, Y.-H. (2021). Learning and Playing in Wubble World. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 4(1), 66-71. https://doi.org/10.1609/aiide.v4i1.18674