DNAKE announced today that Dr. Peng Junren from the Brain-Computer Interaction Division has published a paper titled "Shared autonomy between human electroencephalography and TD3 deep reinforcement learning: A multi-agent copilot approach" in the Annals of the New York Academy of Sciences. According to the survey, about 15%-30% of users are unable to effectively operate traditional brain-computer interface systems due to physiological differences. Existing brain-computer interfaces only calculate human internal brain activity without considering environmental factors. Therefore, DNAKE's Brain-Computer Interaction Division has proposed an active brain-computer interface co-control scheme based on deep reinforcement learning, providing a new paradigm for the universalization of brain-computer interfaces through collaborative decision-making between humans and AI agents. Next, DNAKE will focus on breakthroughs in core technologies for brainwave interaction and their industrialization, promoting the transition of brainwave interaction technology from the laboratory to industrial application