All graph search algorithms to make my life easier
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US: Uninformed Search
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IS: Informed Search (Weighted Graph)
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AS: Adversarial Search (Game Theory)
| Type | Algo | Note | Usage |
|---|---|---|---|
| US | DepthFirstTreeSearch() |
no loop check | dfs = DepthFirstTreeSearch(graph, "E", "B") dfs.without_loop_checking() |
| US | DepthFirstTreeSearch() |
loop check | dfs = DepthFirstTreeSearch(graph, "E", "B") dfs.with_loop_checking() |
| US | DepthFirstTreeSearch() |
limited_depth_search | dfs = DepthFirstTreeSearch(graph, "E", "B") dfs.limited_depth_search(depth=x) |
| US | BreadthFirstSearch() |
solve() | bfs = BreadthFirstSearch(graph, "E", "B") bfs.solve() |
| US | IterativeDeepening() |
solve() | ids = IterativeDeepening(graph2, "Bob", "Gale") ids.solve(max_depth=?) |
| IS | UniformCostSearch() |
solve() | ucs = UniformCostSearch(weighted_graph, ("S", 0), "G") ucs.solve() |
| IS | AStarSearch() |
solve() | a_star = AStarSearch(weighted_graph, ("S", heuristic_table["S"]), "G", heuristic_table) a_star.solve() |
| AS | MiniMax() |
best_move(graph, root, depth) | MiniMax = MiniMax() MiniMax.best_move(game_tree_graph, "A", 3) |
| AS | AlphaBeta() |
best_move(graph, root, depth) | AlphaBeta = AlphaBetaPruning() AlphaBeta.best_move(game_tree_graph, "A", 4) |