  In this paper, we consider the syntactic properties of languages emerged in
referential games, using unsupervised grammar induction (UGI) techniques
originally designed to analyse natural language. We show that the considered
UGI techniques are appropriate to analyse emergent languages and we then study
if the languages that emerge in a typical referential game setup exhibit
syntactic structure, and to what extent this depends on the maximum message
length and number of symbols that the agents are allowed to use. Our
experiments demonstrate that a certain message length and vocabulary size are
required for structure to emerge, but they also illustrate that more
sophisticated game scenarios are required to obtain syntactic properties more
akin to those observed in human language. We argue that UGI techniques should
be part of the standard toolkit for analysing emergent languages and release a
comprehensive library to facilitate such analysis for future researchers.
