USN: a robust imitation learning method against diverse action noise

• المؤلفون الرئيسيون: Yu, Xingrui, Han, Bo, Tsang, Ivor Wai-Hung
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Computer and Information Science; Learning methods; Realistic scenario
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/179928
• المؤسسة: Nanyang Technological University

Learning from imperfect demonstrations is a crucial challenge in imitation learning (IL). Unlike existing works that still rely on the enormous effort of expert demonstrators, we consider a more cost-effective option for obtaining a large number of demonstrations. That is, hire annotators to label a...