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A Computational Model of the Hybrid Bio-Machine MPMS for Ratbots Navigation

机译:机器人导航混合生物机MPMS的计算模型

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As a typical cyborg intelligent system, ratbots possess not only their own biological brain but machine visual sensation, memory, and computation. Electrodes implanted in the medial forebrain bundle (MFB) connect the rat's biological brain with the computer, which presents a hybrid bio-machine parallel memory system in the ratbot. For the novel multiple parallel memory system (MPMS) with real-time MFB stimuli, a computational model is proposed to explain the learning and memory processes underlying the enhanced performance of the ratbots in maze navigation tasks. It's shown that the proposed computational model can predict the finish trial number of the maze learning task, which matches well with behavioral experiments. This work will be helpful to understand the memory and learning mechanisms of cyborg intelligent systems and has the potential significance of optimizing the cognitive performance of these systems as well.
机译:作为典型的半机器人智能系统,鼠人不仅拥有自己的生物大脑,而且还具有机器视觉,记忆和计算功能。植入前脑内侧束(MFB)的电极将大鼠的生物大脑与计算机相连,该计算机在大鼠机器人中提供了一种混合的生物机并行存储系统。对于具有实时MFB刺激的新型多并行存储系统(MPMS),提出了一种计算模型来解释在迷宫导航任务中增强了大鼠机器人性能的学习和存储过程。结果表明,所提出的计算模型可以预测迷宫学习任务的完成次数,与行为实验吻合良好。这项工作将有助于理解电子人的智能系统的记忆和学习机制,并具有优化这些系统的认知性能的潜在意义。

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