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Khuong Tran, Maxwell Standen, Junae Kim, David Bowman, Toby Richer, Ashlesha Akella and Chin-Teng Lin
Organised attacks on a computer system to test existing defences, i.e., penetration testing, have been used extensively to evaluate network security. However, penetration testing is a time-consuming process. Additionally, establishing a strategy that res...
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Marta Ribeiro, Joost Ellerbroek and Jacco Hoekstra
Current investigations into urban aerial mobility, as well as the continuing growth of global air transportation, have renewed interest in conflict detection and resolution (CD&R) methods. The use of drones for applications such as package delivery, ...
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Duy Quang Tran and Sang-Hoon Bae
Advanced deep reinforcement learning shows promise as an approach to addressing continuous control tasks, especially in mixed-autonomy traffic. In this study, we present a deep reinforcement-learning-based model that considers the effectiveness of leadin...
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Yang Sun, Yun Li, Wei Xiong, Zhonghua Yao, Krishna Moniz and Ahmed Zahir
Using Pareto optimization in Multi-Objective Reinforcement Learning (MORL) leads to better learning results for network defense games. This is particularly useful for network security agents, who must often balance several goals when choosing what action...
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