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Inverse Reinforcement Learning with Unknown Reward Model based on Structural Risk Minimization
A simplistic model is less likely to contain the real reward function, while a model with high complexity leads to substantial computation cost and risks overfitting.
Observation-based Optimal Control Law Learning with LQR Reconstruction
Designing controllers to generate various trajectories has been studied for years, while recently, recovering an optimal controller from trajectories receives increasing attention.
Multi-period Optimal Control for Mobile Agents Considering State Unpredictability
This paper aims at the trade-off between the control performance and state unpredictability of mobile agents in long time horizon.
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