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SYSTEM AND METHOD FOR TASK CONTROL BASED ON BAYESIAN META-REINFORCEMENT LEARNING
SYSTEM AND METHOD FOR TASK CONTROL BASED ON BAYESIAN META-REINFORCEMENT LEARNING
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机译：基于贝叶斯元强化学习的任务控制系统和方法
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摘要
Methods, systems, and apparatus, including computer programs encoded on computer storage media for task control based on Bayesian Meta-Reinforcement learning. An exemplary method includes obtaining a base machine learning (ML) model trained based on historical data collected from historical tasks. The base ML model represents a prior distribution of model parameters in a neural network representing control policies. The exemplary method further includes receiving observed data from a new control task; training a task-level ML model based on the base ML model and the observed data, wherein the task-level ML model represents a posterior distribution of the model parameters; sampling, based on the posterior distribution of the model parameters, a set of the model parameters that represent a control policy; and applying the control policy in performing the new control task.
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