Generating Plans Using LRTA

A new category of faster and efficiently planners has been used to solve planning problems, which use heuristic search algorithms to build their plans. One of the first successful planning systems to use this new approach was the Fast Forward (FF) planner, in which many other recent planners have built upon. FF proposed a heuristic function for planning problems and created a strategy that combines the execution of the algorithms Enforced Hill Climbing (EHC) and Best First Search (BFS). Although this method presents an enhanced performance when compared to alternative methods, it has some weaknesses. In this paper we present a new planning method based on LRTA, which is an algorithm guided by heuristics like EHC and is complete as BFS. It has some optimizations like pruning successors during expansion and a heap with maximum capacity to store the states during the search. The authors also developed a test environment for planning algorithms. Experiments carried out in this environment show signicant results when compared to FF.