Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable

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Efficient Hierarchical Reinforcement Learning via Mutual Information Constrained Subgoal Discoveryoviding more effective guidance to the low-level policy. The empirical results on continuous control tasks demonstrate that our proposed method significantly enhances the training efficiency, regardless of the dimensions of the state and action spaces, while ensuring comparable performance to state-of-the-art methods.

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Predefined-Time Synchronization of Complex Networks with Disturbances by Using Sliding Mode Controlbust against disturbances, which aligns more with practical application requirements. (2) The predefined time is set as the sliding mode controller parameter, avoiding overestimation of synchronization time. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed approach.

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Conference proceedings 2024CONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements..