AIOct 31, 2019

Towards A Logical Account of Epistemic Causality

arXiv:1910.14217v1
Originality Synthesis-oriented
AI Analysis

This work addresses a gap in causality reasoning for multi-agent systems, but it appears incremental as it builds on an existing model.

The paper tackles the problem of causality from an agent's perspective in multi-agent contexts by adding an epistemic dimension to an existing formal model, and it proves that epistemic causality differs from objective causality using a counterexample.

Reasoning about observed effects and their causes is important in multi-agent contexts. While there has been much work on causality from an objective standpoint, causality from the point of view of some particular agent has received much less attention. In this paper, we address this issue by incorporating an epistemic dimension to an existing formal model of causality. We define what it means for an agent to know the causes of an effect. Then using a counterexample, we prove that epistemic causality is a different notion from its objective counterpart.

Foundations

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