zlacker

> "Maybe if you had a link to Markus' page I could have a look."

e.g. here: https://www.metalevel.at/tist/ solving the Water Jugs problem (search on the page for "We use iterative deepening to find a shortest solution") finding a list of moves emptying and filling jugs, and using `length(Ms, _)` to find shorter list of moves first.

or here: https://www.metalevel.at/prolog/puzzles under "Wolf and Goat" he writes "You can use Prolog's built-in search strategy to search for a sequence of admissible state transitions that let you reach the desired target state. Use iterative deepening to find a shortest solution. In Prolog, you can easily obtain iterative deepening via length/2, which creates lists of increasing length on backtracking."

>>jodrel+(OP)
Thanks! Yes, it's iterative deepening without a lower bound. The trick is that iterative deepening is used to order the space of proofs so that the shortest proof (path through an SLD-tree) is found first. I use that approach often. The cool thing with it is that it doesn't stop in the first solution and will keep generating new solutions ordered by length of the proof as long as there are any. Some times you really want to know all solutions.

There is a bit of a problem, in that if there is no solution the lack of a lower bound will cause the search to go on forever, or until the search space is exhausted- and you don't want that. If you use a lower bound, on the other hand, you may be cutting the search just short of finding the solution. It's another trade-off.