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In the man-machine co-driving, most of the existing indirect cooperative shared steering control(ICSSC) strategies adopt fixed driver models and are designed based on rules. However, the fixed driver model is difficult to match with the actual situation, and the rule-based strategy is hard to be designed under the multi-dimensional feature input and the multi-objective conditions and require complicated parameters adjustment. A driver model that conforms to the driving characteristics of drivers with actual driving data is established, and an ICSSC strategy is proposed based on reinforcement l...

This study offers a thorough exploration of the effective triage of findings from Java static analysis tools utilizing cutting-edge machine learning techniques.

Looking for the latest Government Contracting News? Read about PNNL Study Demos Deep Reinforcement Learning AI as Proactive Cyber Defense Tool.

The system based on deep reinforcement learning can adapt to defenders' tactics and stop 95% of simulated attacks, according to its developers.

The proliferation of IEEE 802.11 or WiFi networks, and the explosive growth in traffic demands call for solutions to maximize the capacity of WiFi networks. Hence, maximizing the spatial reuse of WiFi networks is critical as doing so allows multiple concurrent transmissions. In this respect, a critical network parameter, Clear Channel Assessment (CCA) threshold, plays a vital role as it dictates whether a node is allowed to transmit after sensing the channel. In this paper, we propose to use Deep Q-network (DQN) under two learning patterns to select the CCA threshold of devices. We further con...