  Various structured argumentation frameworks utilize preferences as part of
their standard inference procedure to enable reasoning with preferences. In
this paper, we consider an inverse of the standard reasoning problem, seeking
to identify what preferences over assumptions could lead to a given set of
conclusions being drawn. We ground our work in the Assumption-Based
Argumentation (ABA) framework, and present an algorithm which computes and
enumerates all possible sets of preferences over the assumptions in the system
from which a desired conflict free set of conclusions can be obtained under a
given semantic. After describing our algorithm, we establish its soundness,
completeness and complexity.

Artificial Intelligence