Latent Exploration for Reinforcement Learning
–Neural Information Processing Systems
While this unstructured exploration has proven successful in numerous tasks, it can be suboptimal for overactuated systems. When multiple actuators, such as motors or muscles, drive behavior, uncorrelated perturbations risk diminishing each other's effect, or modifying the behavior in a task-irrelevant way. While solutions to introduce time correlation across action perturbations exist, introducing correlation across actuators has been largely ignored.
Neural Information Processing Systems
Oct-9-2025, 04:58:58 GMT
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