Abstract: A novel control design problem for a class of non-strict feedback multi-agent systems (MAS) in discrete-time form is studied based on reinforcement learning (RL) and applied to multi-marine ...
Abstract: Learning-based methods have gained popularity for training candidate Control Barrier Functions (CBFs) to satisfy the CBF conditions on a finite set of sampled states. However, since the CBF ...
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