FlashSAC improves training speed and final performance of off-policy RL on high-dimensional robot tasks by reducing update frequency, increasing model scale, and bounding norms to limit critic error accumulation.
Myosuite–a contact-rich simulation suite for musculoskeletal motor control
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4representative citing papers
MBDPO reformulates policy optimization as a diffusion process over searched trajectories in latent world models to reduce misalignment between search and value learning.
Non-uniform replay helps most when replay volume is low; high-entropy sampling remains important, and a truncated geometric distribution delivers better sample efficiency with negligible overhead.
Neuromechanical digital twins—simulated bodies with artificial neural controllers—are maturing into tools that can infer unmeasurable physiological variables, test hypotheses, and link neuroscience with robotics and rehabilitation.
citing papers explorer
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FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control
FlashSAC improves training speed and final performance of off-policy RL on high-dimensional robot tasks by reducing update frequency, increasing model scale, and bounding norms to limit critic error accumulation.
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Scaling World-Model Reinforcement Learning Through Diffusion Policy Optimization
MBDPO reformulates policy optimization as a diffusion process over searched trajectories in latent world models to reduce misalignment between search and value learning.
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When Does Non-Uniform Replay Matter in Reinforcement Learning?
Non-uniform replay helps most when replay volume is low; high-entropy sampling remains important, and a truncated geometric distribution delivers better sample efficiency with negligible overhead.
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The embodied brain: Bridging the brain, body, and behavior with biorealistic neuromechanical models
Neuromechanical digital twins—simulated bodies with artificial neural controllers—are maturing into tools that can infer unmeasurable physiological variables, test hypotheses, and link neuroscience with robotics and rehabilitation.