Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Sui, Yanan"'
Learning an effective policy to control high-dimensional, overactuated systems is a significant challenge for deep reinforcement learning algorithms. Such control scenarios are often observed in the neural control of vertebrate musculoskeletal system
Externí odkaz:
http://arxiv.org/abs/2407.11472
We study the problem of Distributionally Robust Constrained RL (DRC-RL), where the goal is to maximize the expected reward subject to environmental distribution shifts and constraints. This setting captures situations where training and testing envir
Externí odkaz:
http://arxiv.org/abs/2406.15788
Safety is critical when applying reinforcement learning (RL) to real-world problems. As a result, safe RL has emerged as a fundamental and powerful paradigm for optimizing an agent's policy while incorporating notions of safety. A prevalent safe RL a
Externí odkaz:
http://arxiv.org/abs/2402.02025
Sequential optimization methods are often confronted with the curse of dimensionality in high-dimensional spaces. Current approaches under the Gaussian process framework are still burdened by the computational complexity of tracking Gaussian process
Externí odkaz:
http://arxiv.org/abs/2401.02650
Sample efficiency is crucial in optimization, particularly in black-box scenarios characterized by expensive evaluations and zeroth-order feedback. When computing resources are plentiful, Bayesian optimization is often favored over evolution strategi
Externí odkaz:
http://arxiv.org/abs/2401.01579
Modeling and control of the human musculoskeletal system is important for understanding human motor functions, developing embodied intelligence, and optimizing human-robot interaction systems. However, current human musculoskeletal models are restric
Externí odkaz:
http://arxiv.org/abs/2312.05473
Publikováno v:
EMBC2023
Rehabilitation training for patients with motor disabilities usually requires specialized devices in rehabilitation centers. Home-based multi-purpose training would significantly increase treatment accessibility and reduce medical costs. While it is
Externí odkaz:
http://arxiv.org/abs/2305.10642
The detection of human sleep stages is widely used in the diagnosis and intervention of neurological and psychiatric diseases. Some patients with deep brain stimulator implanted could have their neural activities recorded from the deep brain. Sleep s
Externí odkaz:
http://arxiv.org/abs/2302.03227
Safe exploration is a key to applying reinforcement learning (RL) in safety-critical systems. Existing safe exploration methods guaranteed safety under the assumption of regularity, and it has been difficult to apply them to large-scale real problems
Externí odkaz:
http://arxiv.org/abs/2111.04894
Most existing imitation learning approaches assume the demonstrations are drawn from experts who are optimal, but relaxing this assumption enables us to use a wider range of data. Standard imitation learning may learn a suboptimal policy from demonst
Externí odkaz:
http://arxiv.org/abs/2110.14754