Discussion
What is no-good learning?
Answer: A
When a partial assignment is shown to fail, storing it as a no-good prevents the search from reconstructing the same doomed combination by a different route. It is the same idea as clause learning in satisfiability solvers and it can transform performance. Ordering statistics, value pruning and solution caching are different techniques. Converting a failure into a permanent constraint is how a search learns from its own mistakes within a single run.
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