Ease-of-teaching and Language Structure in Emergent Communication

• Author / Creator

  Li, Fushan

• Artificial agents have been shown to learn to communicate when needed to complete a cooperative task. Some level of language structure (e.g., compositionality) has been found in the learned communication protocols. This observed structure is often the result of specific environmental pressures during training. By introducing new agents periodically to replace old ones, sequentially and within a population, we explore a new pressure — ease of teaching — and show its impact on the structure of the resulting language.

• Subjects / Keywords

  • Multi-Agent Reinforcement Learning
  • Machine Learning
  • Artificial Intelligence
  • Emergent Communication

• Graduation date

  Fall 2019

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-p4ep-fp15

• License

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