Consistent epistemic planning for multiagent deep reinforcement learning-Reference-Cited by-同舟云学术

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Consistent epistemic planning for multiagent deep reinforcement learning

Published:2023-10-28 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Wu Peiliang,Luo Shicheng^ORCID,Tian Liqiang,Mao Bingyi,Chen Wenbai

Funder

National Key R &D Program of China

National Natural Science Foundation of China

Beijing Natural Science Foundation

Natural Science Foundation of Hebei Province

Innovation Capability Improvement Plan Project of Hebei Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-023-01989-1.pdf

Reference34 articles.

1. Alshehri A, Miller T, Sonenberg L (2021) Modeling communication of collaborative multiagent system under epistemic planning. Int J Intell Syst 36(10):5959–5980

2. Areces C, Fervari R, Saravia AR et al (2021) Uncertainty-based semantics for multi-agent knowing how logics. arXiv preprint arXiv:2106.11492

3. Baier C, Funke F, Majumdar R (2021) Responsibility attribution in parameterized Markovian models. In: Proceedings of the AAAI conference on artificial intelligence, pp 11734–11743

4. Bolander T, Andersen MB (2011) Epistemic planning for single-and multi-agent systems. J Appl Non-Class Logics 21(1):9–34

5. Buckingham D, Kasenberg D, Scheutz M (2020) Simultaneous representation of knowledge and belief for epistemic planning with belief revision. In: Proceedings of the international conference on principles of knowledge representation and reasoning, vol 17, pp 172–181

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