Learning the Right Abstraction: Neural Reduced Dynamics for Complex Robot Control
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来源：arXiv cs.RO发布时间待核实
arXiv:2608.19375v1 Announce Type: new Abstract: High-fidelity embodied AI simulators provide realistic evaluation of complex robotic systems, but their computational cost limits their direct use for large-scale reinforcement learning campaigns. We advocate the use of less accurate but more expeditious simulations, which might draw on data-driven, e.g., neural dynamics, models.