  Recent research studies communication emergence in communities of deep
network agents assigned a joint task, hoping to gain insights on human language
evolution. We propose here a new task capturing crucial aspects of the human
environment, such as natural object affordances, and of human conversation,
such as full symmetry among the participants. By conducting a thorough
pragmatic and semantic analysis of the emergent protocol, we show that the
agents solve the shared task through genuine bilateral, referential
communication. However, the agents develop multiple idiolects, which makes us
conclude that full symmetry is not a sufficient condition for a common language
to emerge.
