MyoChallenge 2025 introduces standardized table tennis and soccer tasks for musculoskeletal models in the MyoSuite simulation framework to benchmark athletic motor control algorithms.
Mujoco: A physics engine for model-based control
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
verdicts
UNVERDICTED 3representative citing papers
RL policies decompose into information-regularized primitives that compete by requesting state information amounts, with the greediest one acting, yielding better generalization than flat or hierarchical baselines.
Introduces a framework that learns an uncertainty-aware dynamics model and optimizes the policy via automatic differentiation through the model, reporting competitive asymptotic performance with significantly lower sample complexity than baselines on continuous control benchmarks.
citing papers explorer
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MyoChallenge 2025: A New Benchmark for Human Athletic Intelligence
MyoChallenge 2025 introduces standardized table tennis and soccer tasks for musculoskeletal models in the MyoSuite simulation framework to benchmark athletic motor control algorithms.
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Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
RL policies decompose into information-regularized primitives that compete by requesting state information amounts, with the greediest one acting, yielding better generalization than flat or hierarchical baselines.
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Uncertainty-aware Model-based Policy Optimization
Introduces a framework that learns an uncertainty-aware dynamics model and optimizes the policy via automatic differentiation through the model, reporting competitive asymptotic performance with significantly lower sample complexity than baselines on continuous control benchmarks.