ML Anthology

Data-Informed Knowledge and Strategies (Extended Abstract)

Junli Jiang, Pavel Naumov
IJCAI 2023 pp. 6910-6914
doi:10.24963/IJCAI.2023/781 /ijcai/2023/jiang2023ijcai-data/

Abstract

The article proposes a new approach to reasoning about knowledge and strategies in multiagent systems. It emphasizes data, not agents, as the source of strategic knowledge. The approach brings together Armstrong's functional dependency expression from database theory, a data-informed knowledge modality based on a recent work by Baltag and van Benthem, and a newly proposed data-informed strategy modality. The main technical result is a sound and complete logical system that describes the interplay between these three logical operators.

PDF IJCAI Semantic Scholar

Cite

Text

Jiang and Naumov. "Data-Informed Knowledge and Strategies (Extended Abstract)." International Joint Conference on Artificial Intelligence, 2023. doi:10.24963/IJCAI.2023/781

Markdown

[Jiang and Naumov. "Data-Informed Knowledge and Strategies (Extended Abstract)." International Joint Conference on Artificial Intelligence, 2023.](https://mlanthology.org/ijcai/2023/jiang2023ijcai-data/) doi:10.24963/IJCAI.2023/781

BibTeX

@inproceedings{jiang2023ijcai-data,
  title     = {{Data-Informed Knowledge and Strategies (Extended Abstract)}},
  author    = {Jiang, Junli and Naumov, Pavel},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {6910-6914},
  doi       = {10.24963/IJCAI.2023/781},
  url       = {https://mlanthology.org/ijcai/2023/jiang2023ijcai-data/}
}