AILOOct 30, 2020

Thinking About Causation: A Causal Language with Epistemic Operators

arXiv:2010.16217v19 citations
Originality Incremental advance
AI Analysis

This work addresses the need for combined causal-epistemic modeling in fields like AI and philosophy, but it is incremental as it builds on existing causal team semantics.

The paper tackles the problem of integrating causal and epistemic reasoning by proposing a formal framework that extends causal models with epistemic states and adds knowledge and observation operators to the language, resulting in a sound and complete axiomatization.

This paper proposes a formal framework for modeling the interaction of causal and (qualitative) epistemic reasoning. To this purpose, we extend the notion of a causal model with a representation of the epistemic state of an agent. On the side of the object language, we add operators to express knowledge and the act of observing new information. We provide a sound and complete axiomatization of the logic, and discuss the relation of this framework to causal team semantics.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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