Hello, I'm starting to work with the drools-solver to help on a gaming project. Basically, we have a game that works in two modes: 1) a competitive game where humans (or agents) compete with one another on a well defined game board to achieve 24 points by using three (or four) agricultural development tokens. 2. A puzzle, where all 4 players work cooperatively to create an equitable solution, where all 4 players win with at least 24 points by means of our agricultural development tokens. I am starting to work with drools-solver to address the puzzle part of our game. Basically, we are interested in having the solver do two things for us: a) find the optimal solution for our game/puzzle, based upon our requirements [this part seems quite straightforward] and b) getting the total number of solutions that satisfy our constraints. We would like, as well, to be able to inspect these other, sub-optimal, solutions, in order to explore our game and puzzle further. From my reading of the "Solver" API , it looks like we will only be able to get the optimal solution. Does anyone have any suggestions for a workaround in this case? Or is there some functionality in the solver that I am missing? I look forward to your feedback. best wishes, Andrew --------------------------------- Andrew Waterman San Cristóbal de las Casas, Chiapas, Mexico _______________________________________________ rules-users mailing list rules-users(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/rules-users

Thanks for the suggestions Geoffrey! We have a specialized brute force solver that my colleague wrote in Pascal for our problem, but it ignores topographical constraints which is why I got involved. We are thinking now of feeding solutions from that set into your solver as starting solutions, and seeing which ones are/remain viable, and which ones do not.

time to implement a search algorithm as you suggest -- I'll let you know if we start going down that path, it sounds Any information on the XML schema for the configuration files? I'd love to see some more detailed documentation on the how to configure problems for the solver [I sent a different email on this topic to the list last week.]

best wishes, Andrew --------------------------------- Andrew Waterman San Cristóbal de las Casas, Chiapas, Mexico +52 1 967 107 5902 +1 510 342 5693 On Feb 7, 2009, at 7:44 AM, Geoffrey De Smet wrote: > Tabu search (and other local search algorithms such as simulated > annealing) are very good at a) find an optimal solution. > Unfortunately, it can't handle b) get the total number of solutions. > > I 'd recommend a brute force or better yet a branch-and-bound (with > alfa and beta pruning) algorithm for b). > In both cases you can reuse some of the internals of drools-solver: > - your constraint rules in the drl files won't change. > - you can reuse the score mechanism which uses the drools rule engine > Due to the forward-chaining nature of the drools rule engine those > algorithms too can take advantage of the scalibity and performance boost. > > Hey, if you do it right, you can write a BruteForceSolver and/or > BranchAndBoundSolver which would be very welcome as a patch to > drools-solver if you're willing to contribute it :) > > With kind regards, > Geoffrey De Smet > > > Andrew Waterman schreef: >> Hello, >> I'm starting to work with the drools-solver to help on a gaming >> project. Basically, we have a game that works in two modes: 1) a >> competitive game where humans (or agents) compete with one another on >> a well defined game board to achieve 24 points by using three (or >> four) agricultural development tokens. 2. A puzzle, where all 4 >> players work cooperatively to create an equitable solution, where all >> 4 players win with at least 24 points by means of our agricultural >> development tokens. >> I am starting to work with drools-solver to address the puzzle part >> of our game. Basically, we are interested in having the solver do >> two things for us: a) find the optimal solution for our >> game/puzzle, based upon our requirements [this part seems quite >> straightforward] and b) getting the total number of solutions that >> satisfy our constraints. We would like, as well, to be able to >> inspect these other, sub-optimal, solutions, in order to explore our >> game and puzzle further. From my reading of the "Solver" API , it >> looks like we will only be able to get the optimal solution. Does >> anyone have any suggestions for a workaround in this case? Or is >> there some functionality in the solver that I am missing? >> I look forward to your feedback. >> best wishes, >> Andrew >> --------------------------------- >> Andrew Waterman >> San Cristóbal de las Casas, Chiapas, Mexico >> _______________________________________________ >> rules-users mailing list >> rules-users(a)lists.jboss.org >> https://lists.jboss.org/mailman/listinfo/rules-users > > _______________________________________________ > rules-users mailing list > rules-users(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/rules-users _______________________________________________ rules-users mailing list rules-users(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/rules-users