Search and Heuristics
The oldest working idea in artificial intelligence: describe a problem as states and actions, then let a systematic exploration find the path. Which strategy you pick decides whether the answer is optimal, and whether you run out of memory before you find it.
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Problem Solving as Search
25 min · 100 XPFormulating a problem as states, actions, and a goal test; the four criteria every strategy is judged on; and why memory, not time, is what usually stops breadth-first search.
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Heuristics and A*
30 min · 120 XPAdding an estimate of the distance remaining; why greedy search is fast but not optimal; and the admissibility and consistency conditions that make A* provably optimal.
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Local Search and Annealing
25 min · 100 XPWhen the path does not matter and only the final state does: hill climbing, the three ways it gets stuck, random restarts, and the annealing schedule that trades exploration for exploitation.
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