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Dafni Antotsiou

2 accepted papers

2022

Modular Adaptive Policy Selection for Multi- Task Imitation Learning through Task Division

ICRA 2022poster

Deep imitation learning requires many expert demonstrations, which can be hard to obtain, especially when many tasks are involved. However, different tasks often share similarities, so learning them jointly can greatly benefit them and alleviate the need for many demonstrations. But, joint multi-tas…

Cited by 2SourcecodeScholar
2021

Adversarial Imitation Learning with Trajectorial Augmentation and Correction

ICRA 2021poster

Deep Imitation Learning requires a large number of expert demonstrations, which are not always easy to obtain, especially for complex tasks. A way to overcome this shortage of labels is through data augmentation. However, this cannot be easily applied to control tasks due to the sequential nature of…

Cited by 18SourcecodeScholar