  The response speed of a network impacts the efficacy of its actions to
external stimuli. However, for a given bound on the update rate, the
network-response speed is limited by the need to maintain stability. This work
increases the network-response speed without having to increase the update rate
by using delayed self-reinforcement (DSR), where each agent uses its already
available information from the network to strengthen its individual update law.
Example simulation results are presented that show more than an order of
magnitude improvement in the response speed (quantified using the settling
time) with the proposed DSR approach.
