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.
Fushan Li (University of Alberta)
Michael Bowling (University of Alberta / DeepMind)
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