Abstract
Heuristic search is a general problem-solving
method. Some heuristic search algorithms,
like the well-known A?
algorithm, are domainindependent, in the sense that their knowledge
of the problem at-hand is limited to the (1) initial state, (2) state transition operators and their
costs, (3) goal-test function, and (4) black-box
heuristic function that estimates the value of a
state. Prominent examples are A?
and Weighted
A?
. Other heuristic search algorithms are domaindependent, that is, customized to solve problems
from a specific domain. A well-known example
is conflict-directed A?
, which is specifically designed to solve model-based diagnosis problems.
In this paper, we review our recent advancements in
both domain-independent and domain-dependent
heuristic search, and outline several challenging
open questions