Abstarct: In recent years, use of underwater wireless sensor networks (UWSN) to collect data from seabed, attracted many researchers attention. AUVs can be used in underwater missions. These vehicles are equipped with a variety of sensors to collect data in underwater environment. By utilizing of artificial intelligence techniques they can operate without any human intervention or control. The main mission of UWSN is to monitor target field and detect events. Due to stochastic nature of events and environmental parameters, points of interest (POI) in the area must be covered by sensors to observe and report events. Controlling topology characterizes how well a sensing field is monitored and how well each pair of sensors is mutually connected in WSNs. Underwater environment changes, dynamically. For this type of environment centralized control method is not appropriate. Limited communication bandwidth, high bit error rate in underwater communication can lead to limited information that an AUV can acquire from neighborhood area. As a result, in this research a completely decentralized topology control algorithm is proposed with the aim of achieving maximal coverage of POI in 3D underwater environment. The algorithm enables AUVs to autonomously decide on and adjust their speed and direction baxsed on the information collected from their neighbors. Proposed topology control is baxsed on Genetic algorithm. Each AUV selects the best movement at each step by independently executing a Genetic algorithm. In the fitness function, the global average neighborhood degree is used as the upper limit of number of neighbors of each AUV. The experiment in this thesis demonstrates, limiting number of neighbors for each AUV, can lead to larger coverage of the POI. We further show the efficiency of the algorithm in terms of coverage of POI, deployment time, and average traveled distance by the AUVs. It is shown AUVs running GA, can adapt to changing conditions such as the loss of number of AUVs. We also demonstrate that the ambiguity in detecting exact locations of AUVs does not prevent GA from achieving a uniform coverage but requiring AUVs travel longer distances to stabilize.