Ease-of-Teaching and Language Structure from Emergent Communication

June 06, 2019 Β· Declared Dead Β· πŸ› Neural Information Processing Systems

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Authors Fushan Li, Michael Bowling arXiv ID 1906.02403 Category cs.AI: Artificial Intelligence Cross-listed cs.CL, cs.LG, cs.MA Citations 108 Venue Neural Information Processing Systems Last Checked 3 months ago
Abstract
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 such a new pressure -- ease of teaching -- and show its impact on the structure of the resulting language.
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