Ease-of-Teaching and Language Structure from Emergent Communication
June 06, 2019 Β· Declared Dead Β· π Neural Information Processing Systems
"No code URL or promise found in abstract"
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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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