Symmetry-Informed Reinforcement Learning and its Application to Low-Level Attitude Control of Quadrotors
Symmetry is ubiquitous in nature, physics, and mathematics. However, a classical symmetry-agnostic reinforcement learning (RL) approach cannot guarantee to respect symmetry. Researchers have shown that if the symmetry of a system cannot be respected, the performance of a symmetry-agnostic RL approac...
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Veröffentlicht in: | IEEE transactions on artificial intelligence 2024-03, Vol.5 (3), p.1147-1161 |
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