Informed Methods Add Domain-Specific Information
- Add domain-specific information to select what is the best
path to continue searching along
- Define a heuristic function, h(n), that estimates
the "goodness" of a node n. Specifically,
h(n) = estimated cost (or distance) of minimal cost path from
n to a goal state.
- The term heuristic means "serving to aid discovery"
and is an estimate, based on domain-specific information that is
computable from the current state description, of how close we are
to a goal
- Example heuristics:
- Missionaries and Cannibals: Number of people on the starting bank of the river
- 8-puzzle: Number of tiles out of place
- 8-puzzle: Sum of distances each tile is from its goal position
- h(n) >= 0 for all nodes n
- h(n) = 0 implies
that n is a goal node
- h(n) = infinity implies
that n is a deadend from which a goal cannot be reached
- All domain knowledge used in the search is encoded in the
heuristic function h. Consequently, this is an example of
a "weak method" because of the limited way that domain-specific
information is used to solve a problem.