---
title: "Responsibility and Blame: A Structural-Model Approach"
authors:
  - "Hana Chockler"
  - "Joseph Y. Halpern"
doi: ""
url: "https://ijcai.org/proceedings/2003/21"
pdf: "https://ijcai.org/proceedings/2003/0021.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "147-152"
track: ""
keywords:
---

# Responsibility and Blame: A Structural-Model Approach

Hana Chockler, Joseph Y. Halpern

*Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence*, pages 147-152.

## Abstract

Causality is typically treated an aU-or-nothing concept; either A is a cause of B or it is not. We extend the definition of causality introduced by Halpern and Pearl 2001a to take into account the degree of responsibility of A for B. For example, if someone wins an election 11-0, then each person who votes for him is less responsible for the victory than if he had won 6-5. We then define a notion of degree of blame, which takes into account an agent's epistemic state. Roughly speaking, the degree of blame of A for B is the expected degree of responsibility of A forB , taken over the epistemic state of an agent.