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cs.RO2024
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
Kaibo He, Chenhui Zuo, Chengtian Ma +1
Learning an effective policy to control high-dimensional, overactuated systems is a significant challenge for deep reinforcement learning algorithms. Such control scenarios are oft…
cs.LG2024★ 1 cited
Improving sample efficiency of high dimensional Bayesian optimization with MCMC
Zeji Yi, Yunyue Wei, Chu Xin Cheng +2
Sequential optimization methods are often confronted with the curse of dimensionality in high-dimensional spaces. Current approaches under the Gaussian process framework are still…