Towards reconciling usability and usefulness of policy explanations for sequential decision-making systems
Safefy-critical domains often employ autonomous agents which follow a sequential decision-making setup, whereby the agent follows a policy to dictate the appropriate action at each step. AI-practitioners often employ reinforcement learning algorithms to allow an agent to find the best policy. Howeve...
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Published in | Frontiers in robotics and AI Vol. 11; p. 1375490 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
22.07.2024
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Subjects | |
Online Access | Get full text |
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