arXiv AI
Jun 12
A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)
arXiv:2605. 02249v2 Announce Type: replace Abstract: We investigate the belief revision problem in epistemic planning, i.
Explainable Belief Harmonization under Dynamic Epistemic Partitions
arXiv:2607. 21210v1 Announce Type: cross Abstract: Existing approaches to multi-agent belief combination have established mature foundations for combining uncertain beliefs under common assumptions: consensus methods use iterative averaging, logic-based methods resolve conflicting knowledge bases, and epistemic logic analyzes agents' information states.
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arXiv AI
Jul 14
Replicating Belief, Not Bits: Epistemic State Replication for Agentic Systems
arXiv:2607. 09748v1 Announce Type: new Abstract: In distributed systems, the classical State Machine Replication (SMR) model assumes that correct replicas execute deterministic transitions to yield identical bitwise states.
arXiv AI
Sep 24
Preregistered Belief Revision Contracts
The paper introduces Preregistered Belief Revision Contracts (PBRC), a protocol that separates open communication from admissible epistemic change in deliberative multi-agent systems. PBRC fixes evidence triggers, revision operators, priority rules, and fallback policies, requiring that belief changes cite preregistered triggers and validated evidence tokens. The authors prove that PBRC prevents confidence inflation from conformity, preserves auditability, ensures epistemic accountability, and characterizes enforced belief trajectories under token-invariant contracts.
arXiv AI
Aug 25
An Information-Flow Perspective on Explainability Requirements: Specification and Verification
The paper proposes an information‑flow perspective on explainability, arguing that exposing reasons for observed effects is a positive flow of information that must be specified and verified. It introduces an epistemic temporal logic with counterfactual causes to formalize the requirement that agents gain knowledge about why an effect occurred, and presents an algorithm for checking finite‑state models against these specifications. A prototype implementation is evaluated on benchmarks, demonstrating the ability to distinguish explainable from unexplainable systems and to incorporate privacy constraints.
arXiv AI
Jul 1
Belief Contraction in Dynamic Epistemic Logic
arXiv:2606. 31861v1 Announce Type: cross Abstract: Dynamic epistemic logic represents belief change via model transformations induced by epistemic events.
arXiv AI
Jul 24
A New Well-Supported Semantics for Description Logic Programs
arXiv:2607. 21203v1 Announce Type: new Abstract: Description logic programs are a powerful formalism for combining rules with ontologies.
arXiv AI
Jul 1
Better Understanding, Understanding Better
arXiv:2606. 31892v1 Announce Type: cross Abstract: "Any fool can know; the point is to understand.
arXiv AI
Jun 2
An Abstract Worlds Semantic Framework for Belief Change Operators
arXiv:2606. 02163v1 Announce Type: new Abstract: This article proposes a set-theoretic framework for belief change, called Abstract Worlds Semantics, in which no logical syntax is assumed.
arXiv AI
Jul 24
Explainability Framework for Policy-Aware Autonomous Agents
arXiv:2607. 21209v1 Announce Type: cross Abstract: In the field of Artificial Intelligence, an agent is a system which is able to autonomously make decisions in order to reach a desired goal.
arXiv AI
Sep 23
Epi-Logic: A Conceptual Framework for Epistemic Runtime Control, Schema Validity Checking, and Controlled Accommodation in Autonomous AI Agents
arXiv:2609.24755v1 Announce Type: new Abstract: Autonomous AI agents are increasingly deployed in areas where wrong decisions are hard to reverse. This paper examines schema mismatch: the condition i...
Hugging Face Trending Papers
Jul 23
A New Well-Supported Semantics for Description Logic Programs
Description logic programs are a powerful formalism for combining rules with ontologies. The well-supported semantics for description logic programs ensures that no answer sets rely on cyclic dependencies.
arXiv AI
Sep 10
Evidential-Based Higher-Order Set Argumentation Framework
The paper introduces the Evidential-Based Higher-Order Set Argumentation Framework (EHSAF), a unified formalism that extends Dung’s abstract argumentation by incorporating evidential support, higher-order relations, and collective interactions. Two complete semantics are defined: an adjacent complete labelling semantics allowing multiple truth values for arguments in support cycles, and an extension-based complete semantics that accepts only well‑founded support chains. The authors provide a propositional encoding in three‑valued Łukasiewicz logic and extend it to continuous fuzzy logics, proving key properties and showing equivalence under support‑acyclicity.