Planning and Reinforcement Learning for General-Purpose Service Robots
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 4895-4896.
https://doi.org/10.24963/ijcai.2021/679
Keywords
- Robotics: Learning in Robotics
- Planning and Scheduling: Robot Planning
- Robotics: Cognitive Robotics
- Machine Learning: Reinforcement Learning
Abstract
Despite recent progress in AI and robotics research, especially learned robot skills, there remain significant challenges in building robust, scalable, and general-purpose systems for service robots. This Ph.D. research aims to combine symbolic planning and reinforcement learning to reason about high-level robot tasks and adapt to the real world. We will introduce task planning algorithms that adapt to the environment and other agents, as well as reinforcement learning methods that are practical for service robot systems. Taken together, this work will make a significant step towards creating general-purpose service robots.
@inproceedings{ijcai2021p679,
title = {Planning and Reinforcement Learning for General-Purpose Service Robots},
author = {Jiang, Yuqian},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Prof. Zhi-Hua Zhou},
pages = {4895--4896},
year = {2021},
month = {8},
note = {Doctoral Consortium},
doi = {10.24963/ijcai.2021/679},
url = {https://doi.org/10.24963/ijcai.2021/679},
}
TY - CPAPER TI - Planning and Reinforcement Learning for General-Purpose Service Robots AU - Jiang, Yuqian T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 4895 EP - 4896 DO - 10.24963/ijcai.2021/679 UR - https://doi.org/10.24963/ijcai.2021/679 ER -Copied
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