In this paper, we propose a Q-learning based delay-aware routing (QDAR) algorithm to extend the lifetime of underwater sensor networks.  In QDAR, a data collection phase is designed to adapt to the dynamic environment.  With the application of the Q-learning technique, QDAR can determine a global optimal next hop rather than a greedy one.  Thus, the QDAR algorithm can extend the network lifetime by uniformly distributing the residual energy and provide lower end-to-end delay. 
QDAR
A Q-Learning-Based Delay-Aware Routing Algorithm to Extend the Lifetime of Underwater Sensor Networks.Underwater sensor networks (UWSNs) have become a hot research topic because of their various aquatic applications.  In this paper, we propose a Q-learning based delay-aware routing (QDAR) algorithm to extend the lifetime of underwater sensor networks.  With the application of the Q-learning technique, QDAR can determine a global optimal next hop rather than a greedy one. 
Q-learning