On the Spontaneous Emergence of Discrete and Compositional Signals
Table 2: Discreteness in production, as measured by F1 scores for automatically clusterized messages.
['[EMPTY]', '[BOLD] Shared', '[BOLD] Non-shared']
First, we sample 100 contexts, and collect the output of the trained encoder for each of these contexts combined with each possible function A label is assigned to each cluster using the ground truth: the label of a cluster is the function f that was most often at the source of a point in this cluster. The model reached near-optimal clusterization measures in 7 out of 8 parameter settings, with the Non-strict, Non-shared context with 5 objects being the exception.