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In the study of path-finding problems in artificial intelligence, a heuristic function is said to be consistent, or monotone, if its estimate is always less than or equal to the estimated distance from any neighbouring vertex to the goal, plus the cost of reaching that neighbour.
Art, Consequences of monotonicity & Overview
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heuristic consistent displaystyle cost node admissible goal path always reaching true estimate equal estimated i-1 since also non-decreasing optimal expansion
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Consistent heuristic | related to Consequences of monotonicity | Consistent | 0.60 | section |
| Consistent heuristic | related to Consequences of monotonicity | It's | 0.60 | section |
| Consistent heuristic | related to Consequences of monotonicity | The | 0.60 | section |
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