Modeling Responsibility Attribution in a Group

Attributing responsibilities to a group of agents who contribute to a collective cause

is common in our daily life. While we as humans could relatively efficiently assign

responsibility to others using our intuition, the wide range of possible scenarios and

complexity of our cognitive mechanisms should not be overlooked. Understanding

of how rational responsibility judgments are made could expand our knowledge

about human causal and moral reasoning. Over recent years, a few theories have

been developed to account for responsibility attribution, but they have various theoretical

and empirical limitations. In this thesis, an extended computational model

is proposed in an effort to expand the explanatory power of previous models. We

devised two sets of experiments to test the performance of this newmodel, especially

with regards to aspects including (1) epistemic state of rater, (2) perceived autonomy

of agents, and (3) value range of contributions. Our results suggest that the new

model demonstrated reasonable power in predicting responsibility attribution, albeit

with several unexpected inaccuracies. The close relationship among responsibility,

criticality, and pivotality is nonetheless supported.