Self-Adaptive Swarm System (SASS)

Yang, Qin

doi:10.24963/ijcai.2021/722

Self-Adaptive Swarm System (SASS)

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 5040-5041.

https://doi.org/10.24963/ijcai.2021/722

Keywords

Uncertainty in AI: Bayesian Networks
Robotics: Multi-Robot Systems
Machine Learning: Bayesian Learning
Agent-based and Multi-agent Systems: Agent Theories and Models

Abstract

Distributed artificial intelligence (DAI) studies artificial intelligence entities working together to reason, plan, solve problems, organize behaviors and strategies, make collective decisions and learn. This Ph.D. research proposes a principled Multi-Agent Systems (MAS) cooperation framework -- Self-Adaptive Swarm System (SASS) -- to bridge the fourth level automation gap between perception, communication, planning, execution, decision-making, and learning.

Qin Yang. 2021. Self-Adaptive Swarm System (SASS). In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 5040–5041. https://doi.org/10.24963/ijcai.2021/722

@inproceedings{ijcai2021p722,
  title     = {Self-Adaptive Swarm System (SASS)},
  author    = {Yang, Qin},
  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     = {5040--5041},
  year      = {2021},
  month     = {8},
  note      = {Doctoral Consortium},
  doi       = {10.24963/ijcai.2021/722},
  url       = {https://doi.org/10.24963/ijcai.2021/722},
}

TY  - CPAPER
TI  - Self-Adaptive Swarm System (SASS)
AU  - Yang, Qin
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 5040
EP  - 5041
DO  - 10.24963/ijcai.2021/722
UR  - https://doi.org/10.24963/ijcai.2021/722
ER  -