Wetlands are an important part of the ecological system, providing a myriad of benefits for people, wildlife, and the environment. They also serve as “nature’s kidneys,” filtering out pollutants from surface water. A new study from the University of Illinois Urbana-Champaign finds that wetlands along the Mississippi River Basin effectively clean up nitrogen runoff from agricultural fields. The researchers also show this can lead to significant savings for local drinking water treatment facilities.

The exploration-exploitation dilemma is a long-standing topic in deep reinforcement learning. In recent research, a noise-driven enhancement for exploration algorithm has proposed for UAV autonomous navigation. This algorithm introduces a differentiated exploration noise control strategy based on the global navigation training hit rate and the specific situations encountered by the UAV in each episode. Furthermore, it designs a noise dual experience replay buffer to amplify the distinct effects of noisy and deterministic experiences. This approach reduces the computational cost associated with excessive exploration and mitigates the problem of the navigation policy converging to a local optimum.