Publication at Faculty of Mathematics and Physics |
2015
Abstract
Logic programming provides a declarative framework for modeling and solving many combinatorial problems. Until recently, it was not competitive with state of the art planning techniques partly due to search capabilities limited to backtracking.
Recent development brought more advanced search techniques to logic programming such as tabling that simplifies implementation and exploitation of more sophisticated search algorithms. Together with rich modeling capabilities this progress brings tabled logic programing on a par with current best planners.
The paper brings an initial experimental study comparing various approaches to search for sequential plans in the Picat planning module.