Abstract
Causality is typically treated an all-or-nothing con-cept; 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 cpis-temic state. Roughly speaking, the degree of blame of A for D is the expected degree of responsibil-ity of A for B, taken over the epistemic state of an agent.
Original language | English |
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Title of host publication | IJCAI-03, Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence |
Publisher | Morgan Kaufmann Publishers Inc. |
Pages | 147-153 |
Publication status | Published - 2003 |