Abstract: When encountering the distribution shift between the source (training) and target (test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different ...
Optimal Control for Constrained Discrete-Time Nonlinear Systems Based on Safe Reinforcement Learning
The state and input constraints of nonlinear systems could greatly impede the realization of their optimal control when using reinforcement learning (RL)-based approaches since the commonly used ...
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