LaCroix, Travis
(2020)
Communicative Bottlenecks Lead to Maximal Information Transfer.
Journal of Experimental and Theoretical Artificial Intelligence.
Abstract
This paper presents new analytic and numerical analysis of signalling games that give rise to informational bottlenecks—that is to say, signalling games with more state/act pairs than available signals to communicate information about the world. I show via simulation that agents learning to coordinate tend to favour partitions of nature which provide maximal information transfer. This is true despite the fact that nothing from an initial analysis of the stability properties of the underlying signalling game suggests that this should be the case. As a first pass to explain this, I note that the underlying structure of our model favours maximal information transfer in regard to the simple combinatorial properties of how the agents might partition nature into kinds. However, I suggest that this does not perfectly capture the empirical results; thus, several open questions remain.
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