  We describe the Inspire system which participated in the first competition on
Inductive Logic Programming (ILP). Inspire is based on Answer Set Programming
(ASP). The distinguishing feature of Inspire is an ASP encoding for hypothesis
space generation: given a set of facts representing the mode bias, and a set of
cost configuration parameters, each answer set of this encoding represents a
single rule that is considered for finding a hypothesis that entails the given
examples. Compared with state-of-the-art methods that use the length of the
rule body as a metric for rule complexity, our approach permits a much more
fine-grained specification of the shape of hypothesis candidate rules. The
Inspire system iteratively increases the rule cost limit and thereby increases
the search space until it finds a suitable hypothesis. The system searches for
a hypothesis that entails a single example at a time, utilizing an ASP encoding
derived from the encoding used in XHAIL. We perform experiments with the
development and test set of the ILP competition. For comparison we also adapted
the ILASP system to process competition instances. Experimental results show
that the cost parameters for the hypothesis search space are an important
factor for finding hypotheses to competition instances within tight resource
bounds.
