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.