Communicating in Emergent Language with an Induced Morphological Phrasebook

We build rule-based emergent language (EL) agents using form–meaning mappings induced from ELs (“morphological phrasebooks”) and test their communicative performance in the EL environment with its neural network agents. This contributes three things: First, it assesses the quality of the morphemes discovered by the induction algorithm in situ , which we find to be effective for communicating in the EL. Second, it allows us to uncover morphosyntactic properties of EL through ablating the algorithms which induce and utilize morphemes, showing that the ELs rely on repetition as well as morpheme ordering to convey meaning. Third, we find that the normalized pointwise mutual information of forms and meanings in the mor-phemes serves as a metric of compositionality that is more closely correlated with the ability of the phrasebook-agents to “speak” and “hear” an EL than existing metrics such as topographic similarity.