A system and method are disclosed for big bucket campaign planning that automatically learns weights for parameters of a weighted evaluation function. Embodiments include modeling the use of the one or more campaign operations and one or more campaignable resources as one or more campaign planning problems comprising a sequential decision problem with decision parameters, determining a campaign plan for the use of campaign operations and one or more campaignable resource, encoding a required policy of the sequential decision problem into a k-lookahead search strategy by defining an evaluation function comprising a weighted sum of features evaluated from the campaign planning problem, learning weights associated with an evaluation function that determines an effective objective function for campaign planning as a linear programming problem, and computing the parameters of the evaluation function using an iterative cross-entropy campaign planning.