Ease-of-Teaching and Language Structure from Emergent Communication

Part of Advances in Neural Information Processing Systems 32 (NeurIPS 2019)

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Fushan Li, Michael Bowling


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.