KR2023Proceedings of the 20th International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning

Rhodes, Greece. September 2-8, 2023.

Edited by

ISSN: 2334-1033
ISBN: 978-1-956792-02-7

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Copyright © 2023 International Joint Conferences on Artificial Intelligence Organization

A Belief Model for Conflicting and Uncertain Evidence: Connecting Dempster-Shafer Theory and the Topology of Evidence

  1. Daira Pinto Prieto(University of Amsterdam)
  2. Ronald de Haan(University of Amsterdam)
  3. Aybüke Özgün(University of Amsterdam)


  1. Belief revision and update, belief merging, information fusion
  2. Uncertainty, vagueness, many-valued and fuzzy logics
  3. Reasoning about knowledge, beliefs, and other mental attitudes
  4. Computational aspects of knowledge representation


One problem to solve in the context of information fusion, decision-making, and other artificial intelligence challenges is to compute justified beliefs based on evidence. In real-life examples, this evidence may be inconsistent, incomplete, or uncertain, making the problem of evidence fusion highly non-trivial. In this paper, we propose a new model for measuring degrees of beliefs based on possibly inconsistent, incomplete, and uncertain evidence, by combining tools from Dempster-Shafer Theory and Topological Models of Evidence. Our belief model is more general than the aforementioned approaches in two important ways: (1) it can reproduce them when appropriate constraints are imposed, and, more notably, (2) it is flexible enough to compute beliefs according to various standards that represent agents' evidential demands. The latter novelty allows the users of our model to employ it to compute an agent's (possibly) distinct degrees of belief, based on the same evidence, in situations when, e.g, the agent prioritizes avoiding false negatives and when it prioritizes avoiding false positives. Finally, we show that computing degree of belief with this model is #P-complete in general.