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Can Network Models of Science Do Without Pluralist Agents? — arXiv:2611.04590

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.04590
License (as archived): CC0-1.0
Archived: 2026-11-04T18:32:22.834Z
SHA-256 of the archived text: 0297cd0cacbf5c6c383ab81a2f1fd2761db5b96d8d0a3ca9d9bd4619e6c608d0
Stable URL of this page: https://metraipolis.com/documento/dc_5b00a814abec

How to cite

Can Network Models of Science Do Without Pluralist Agents? — arXiv:2611.04590 — arXiv (en), https://arxiv.org/abs/2611.04590 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_5b00a814abec (Metraipolis archive dc_5b00a814abec, sha256 0297cd0cacbf5c6c383ab81a2f1fd2761db5b96d8d0a3ca9d9bd4619e6c608d0)

BibTeX

@misc{dc5b00a814abec,
  title = {Can Network Models of Science Do Without Pluralist Agents? — arXiv:2611.04590},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.04590},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_5b00a814abec; sha256 0297cd0cacbf5c6c383ab81a2f1fd2761db5b96d8d0a3ca9d9bd4619e6c608d0},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.04590. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Science is a process of useful models being proven wrong time and again, but despite its many flaws, it somehow works. Why is this? Paul Feyerabend argued that it works because people dare to hold and defend incompatible rival theories against the accepted one, since a theory's failures often lead to its abandonment in the presence of a more accurate or simpler alternative. He called this view theoretical pluralism. We introduce a theoretical and experimental model in which this can be examined. It compares communities of pluralist agents, which can hold rival theories side by side and maintain beliefs within and between those theories, with communities of monist agents, which can only incorporate what they hear or observe into a single model of their own. In a multi-agent variational inference setting, our experimental demonstrations illustrate how communities with rival theories can go through periods of uncertainty followed by a shift in the theories they hold true, how the information that is communicated between communities affects beliefs when those communities make different observations about the world, and how sharing support for theories and sharing beliefs within them contribute differently to collective belief dynamics.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.MA, nuovi lavori del giorno).
Categorie arXiv: Multiagent Systems (cs.MA) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2611.04590 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-04T18:32:22.193Z dalla pagina https://arxiv.org/list/cs.MA/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).