Blameworthiness in Multi-Agent Settings
Abstract
We provide a formal definition of blameworthiness in settings where multiple agents can collaborate to avoid a negative outcome. We first provide a method for ascribing blameworthiness to groups relative to an epistemic state (a distribution over causal models that describe how the outcome might arise). We then show how we can go from an ascription of blameworthiness for groups to an ascription of blameworthiness for individuals using a standard notion from cooperative game theory, the Shapley value. We believe that getting a good notion of blameworthiness in a group setting will be critical for designing autonomous agents that behave in a moral manner.
Cite
Text
Friedenberg and Halpern. "Blameworthiness in Multi-Agent Settings." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.3301525Markdown
[Friedenberg and Halpern. "Blameworthiness in Multi-Agent Settings." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/friedenberg2019aaai-blameworthiness/) doi:10.1609/AAAI.V33I01.3301525BibTeX
@inproceedings{friedenberg2019aaai-blameworthiness,
title = {{Blameworthiness in Multi-Agent Settings}},
author = {Friedenberg, Meir and Halpern, Joseph Y.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {525-532},
doi = {10.1609/AAAI.V33I01.3301525},
url = {https://mlanthology.org/aaai/2019/friedenberg2019aaai-blameworthiness/}
}