SEQUENTIAL LEARNING OF CONSTRAINTS FOR HIERARCHICAL REINFORCEMENT LEARNING
A computer-implemented method, computer program product, and computer processing system are provided for Hierarchical Reinforcement Learning (HRL) with a target task. The method includes obtaining, by a processor device, a sequence of tasks based on hierarchical relations between the tasks, the task...
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Main Authors | , , , |
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Format | Patent |
Language | English |
Published |
30.01.2020
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Subjects | |
Online Access | Get full text |
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Summary: | A computer-implemented method, computer program product, and computer processing system are provided for Hierarchical Reinforcement Learning (HRL) with a target task. The method includes obtaining, by a processor device, a sequence of tasks based on hierarchical relations between the tasks, the tasks constituting the target task. The method further includes learning, by a processor device, a sequence of constraints corresponding to the sequence of tasks by repeating, for each of the tasks in the sequence, reinforcement learning and supervised learning with a set of good samples and a set of bad samples and by applying an obtained constraint for a current task to a next task. |
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Bibliography: | Application Number: US201816048569 |