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3 cards from this section. Quick, good the night before a test.
What does g(n) represent in A* search?
Think about the distance covered so far.
Is A* search complete?
Think about the guarantees that A* provides.
What does A* search primarily use to evaluate paths?
Consider the definition of the cost function f(n).
True or False: A* search can find optimal solutions using any heuristic.
Remember the conditions for the optimality of A*.
Implement a basic A* search algorithm in a programming language of your choice. Use a simple grid layout where certain cells are obstacles. Explain the choice of your heuristic functions.
Start with a straightforward grid and incrementally add obstacles to see how the path changes.
Discuss the potential impacts of an inadmissible heuristic on the results produced by A*. What could happen if the heuristic significantly overestimates the cost?
Consider how overestimating alters the way A* ranks its paths.
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