{"type":"ScholarlyArticle","title":"Responsibility and Blame: A Structural-Model Approach","authors":[{"name":"Hana Chockler","slug":"hana-chockler","given":"Hana","family":"Chockler","affiliation":""},{"name":"Joseph Y. Halpern","slug":"joseph-y-halpern","given":"Joseph Y.","family":"Halpern","affiliation":""}],"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.","doi":null,"url":"https://ijcai.org/proceedings/2003/21","pdf":"https://ijcai.org/proceedings/2003/0021.pdf","markdown":"https://ijcai.org/proceedings/2003/21.md","bibtex":"https://ijcai.org/proceedings/2003/bibtex/21","volume":{"slug":"2003","title":"Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2003","url":"https://ijcai.org/proceedings/2003/","year":2003,"location":"Acapulco, Mexico","dates":"","editors":"Georg Gottlob","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":21,"pages":{"first":147,"last":152},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}