Classification of Strategies for State Space Search

Towards the solution:
Complete – strategy is guaranteed to find a solution path, provided such a path exists
admissible - strategy is guaranteed to find the cheapest solution path;
defensible - strategy is guaranteed to find the shortest solution path;
concessible - strategy is not guaranteed to find the cheapest or the shortest solution path although it may occasionally do so;
Incomplete


Towards the use of heuristics:
Blind (exhaustive, uninformed, naive) – explore the state space systematically without any “suspicion” where the final state might be and direction of the search to it.
Breadth-first search;
Depth-first search (depth-first search with leap-frogging (or just depth-first search), depth-first search with backtracking (or just Backtracking)
Uniform-cost search;
Iterative deepening;
Etc.
Heuristic (informed)- exploit state descriptions to select the “most promising” node

Classification of Strategies for State Space Search

Towards the use of heuristics:
Blind (exhaustive, uninformed, naive) – explore the state space systematically without any “suspicion” where the final state might be and direction of the search to it.
Breadth-first search;
Depth-first search (depth-first search with leap-frogging (or just depth-first search), depth-first search with backtracking (or just Backtracking)
Uniform-cost search;
Iterative deepening;
Etc.
Heuristic (informed)- exploit state descriptions to select the “most promising” node

Classification of Strategies for State Space Search

Blind (exhaustive, uninformed, naive) – explore the state space systematically without any “suspicion” where the final state might be and direction of the search to it.
Breadth-first search;
Depth-first search (depth-first search with leap-frogging (or just depth-first search), depth-first search with backtracking (or just Backtracking)
Uniform-cost search;
Iterative deepening;
Etc.
Heuristic (informed)- exploit state descriptions to select the “most promising” node