  The demand on the underwater communications is extremely increasing in
searching for underwater resources, marine expedition, or environmental
researches, yet there are many problems with the wireless communications
because of the characteristics of the underwater environments. Especially, with
the underwater wireless networks, there happen inevitable delay time and
spacial inequality due to the distances between the nodes. To solve these
problems, this paper suggests a new solution based on ALOHA-Q. The suggested
method use random NAV value. and Environments take reward through
communications success or fail. After then, The environments setting NAV value
from reward. This model minimizes usage of energy and computing resources under
the underwater wireless networks, and learns and setting NAV values through
intense learning. The results of the simulations show that NAV values can be
environmentally adopted and select best value to the circumstances, so the
problems which are unnecessary delay times and spacial inequality can be
solved. Result of simulations, NAV time decreasing 17.5% compared with original
NAV.
