Responsibility and Blame: A Structural-Model Approach

Chockler, Hana; Halpern, Joseph Y.

Responsibility and Blame: A Structural-Model Approach

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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.

Hana Chockler, and Joseph Y. Halpern. 2003. Responsibility and Blame: A Structural-Model Approach. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03. IJCAI, 147–152. https://ijcai.org/proceedings/2003/21

@inproceedings{ijcai2003p21,
  title     = {Responsibility and Blame: A Structural-Model Approach},
  author    = {Chockler, Hana and Halpern, Joseph Y.},
  booktitle = {Proceedings of the Eighteenth International Joint Conference on
               Artificial Intelligence, {IJCAI-03}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Georg Gottlob},
  pages     = {147--152},
  year      = {2003},
  url       = {https://ijcai.org/proceedings/2003/21},
}

TY  - CPAPER
TI  - Responsibility and Blame: A Structural-Model Approach
AU  - Chockler, Hana
AU  - Halpern, Joseph Y.
T2  - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2003
SP  - 147
EP  - 152
UR  - https://ijcai.org/proceedings/2003/21
ER  -