MonteCarlo Tree Search with Goal-Based Heuristic

The use of a domain-driven symbolic planner may provide in- teresting performances, even with the most challenging plan- ning domain. However, sometimes a domain utility-function to be maximized does not exist: there are cases in which cre- ating such a function is difficult and error-prone. This paper investigates an alternative approach to afford deterministic planning when no utility-functions are available. In cases like these, classical planning may provide bad performances. The use of a MonteCarlo approach, in conjunction with a goal- based heuristic, has given promising results.