Abstract
Judgment aggregation (JA) studies how to aggregate
truth valuations on logically related issues. Computing the outcome of aggregation procedures is notoriously computationally hard, which is the likely reason that no implementation of them exists as of yet.
However, even hard problems sometimes need to be
solved. The worst-case computational complexity
of answer set programming (ASP) matches that of
most problems in judgment aggregation. We take
advantage of this and propose a natural and modular
encoding of various judgment aggregation procedures and related problems in JA into ASP. With
these encodings, we achieve two results: (1) paving
the way towards constructing a wide range of new
benchmark instances (from JA) for answer set solving algorithms; and (2) providing an automated tool
for researchers in the area of judgment aggregation