2026 AAAI AAAI 2026

A Logical Analysis of an Information Filtering Architecture Based on Epistemic Trust Inference

Abstract

Abstract In agent theory, epistemic trust is used to infer beliefs, for example by filtering out the information the agent receives from untrustworthy agents. Moreover, trust itself can be inferred from other information. We introduce a simple information filtering architecture that clearly distinguishes the relation between the two kinds of inference. We provide a logical analysis of the architecture, based on a new family of input/output logics. We then explore information filtering and belief manipulation within this formal framework. Our key finding is that with this architecture, some of the widely debated logical rules for trust inference are redundant with respect to information-filtering mechanisms and some others are redundant with respect to belief manipulation.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Knowledge & Reasoning
🧭 Keyword Pioneer — epistemic trust
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Reinforcement Learning