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Towards a safe Society 5.0: Reinforcement learning pentesting agent training in realistic network environments
More information: Huynh Phuong Thanh Nguyen et al, PenGym: Realistic training environment for reinforcement learning pentesting agents, Computers & Security (2024). DOI: 10.1016/j.cose.2024.104140 ...
unite16d
DeepSeek-R1: Transforming AI Reasoning with Reinforcement Learning
DeepSeek-R1 is the groundbreaking reasoning model introduced by China-based DeepSeek AI Lab. This model sets a new benchmark in reasoning capabilities for open-source AI. As detailed in the ...
devdiscourse12d
The silent saboteur: Action-level backdoor attacks in deep reinforcement learning
To counter the sophisticated threats posed by advanced backdoor frameworks like UNIDOOR, the study underscores the importance ...
Science Daily18d
New training approach could help AI agents perform better in uncertain conditions
AI agents trained in simulations that differ from the environments where they are deployed sometimes perform better than agents trained and deployed in the same environment, research shows.