A note on social learning in non-atomic routing games

Abstract

This work expands on the existing body of research about Social Learning in Dynamic Non-atomic Routing Games to include infinite capacity multi-commodity instances and capacitated instances with one or more commodities. We define when a network state is identifiable, and show the network conditions sufficient to achieve almost sure learning. In capacitated instances, a sufficient condition to achieve learning is that the network respects a condition called weak capacity conservation, that is independent on the network topology. In infinite capacity instances, a sufficient condition is that the network is series-parallel in each commodity sub-network.