Full Echo Q-routing with adaptive learning rates: A reinforcement learning approach to network routing

Abstract

Dynamically changing networks, such as mobile wireless sensor networks, Internet of Things networks, vehicular ad hoc networks etc., require efficient routing techniques. We present a routing algorithm, Adaptive Q-routing Full Echo, that is an extension of `full echo' modification of Q-routing algorithm and uses adaptive learning rates to improve exploration behaviour. The performance of the proposed algorithm is evaluated empirically in comparison to Q-routing and Dual Q-routing algorithms. The preliminary results suggest that the proposed algorithm represents a promising way of achieving good routing performance in dynamically changing networks.