heuristic search

For hierarchical networks, searches {search, computer} {computer search} can go first to lower nodes {depth first search}, stay at same level {breadth first search}, or use evaluation function {heuristic search}|. Heuristic search tries to reach goal. It starts from current situation, evaluates nearby situations to short depth to see if goal is closer or farther, chooses only nearby situations that are closer, and then repeats, until exhausting all new nearby situations or finding goal.

evaluation

Evaluation uses scoring methods. Searching requires assigning probabilities. Search eliminates nodes by checking if they have successors, by assigning scores, or by checking for duplicates. Search can minimize risk {minimax, search}. Heuristic search can evaluate search steps to decide whether to go backward or forward {Shannon paradigm}. Search can use other strategies {set-of-support strategy} {unit preference strategy} {linear input form strategy} {ancestry-filtered strategy}.

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Date Modified: 2022.0224