Learning approximate preconditions for methods in hierarchical plans

TitleLearning approximate preconditions for methods in hierarchical plans
Publication TypeConference Papers
Year of Publication2005
AuthorsIlghami O, Muñoz-Avila H, Nau DS, Aha DW
Date Published2005///
Conference LocationNew York, NY, USA
ISBN Number1-59593-180-5

A significant challenge in developing planning systems for practical applications is the difficulty of acquiring the domain knowledge needed by such systems. One method for acquiring this knowledge is to learn it from plan traces, but this method typically requires a huge number of plan traces to converge. In this paper, we show that the problem with slow convergence can be circumvented by having the learner generate solution plans even before the planning domain is completely learned. Our empirical results show that these improvements reduce the size of the training set that is needed to find correct answers to a large percentage of planning problems in the test set.