Using Tabled Logic Programming to Solve the Petrobras Planning Problem
  Tabling has been used for some time to improve efficiency of Prolog programs
by memorizing answered queries. The same idea can be naturally used to memorize
visited states during search for planning. In this paper we present a planner
developed in the Picat language to solve the Petrobras planning problem. Picat
is a novel Prolog-like language that provides pattern matching, deterministic
and non-deterministic rules, and tabling as its core modelling and solving
features. We demonstrate these capabilities using the Petrobras problem, where
the goal is to plan transport of cargo items from ports to platforms using
vessels with limited capacity. Monte Carlo Tree Search has been so far the best
technique to tackle this problem and we will show that by using tabling we can
achieve much better runtime efficiency and better plan quality.
