Heuristic search-based replanning

Abstract

Many real-world planning problems require one to solve a series of similar planning tasks. In this case, replanning can be much faster than planning from scratch. In this paper, we introduce a novel replanning method for symbolic planning with heuristic search-based planners, currently the most pop-ular planners. Our SHERPA replanner is not only the first heuristic search-based replanner but, different from previous replanners for other planning paradigms, it also guarantees that the quality of its plans is as good as that achieved by planning from scratch. We provide an experimental feasi-bility study that demonstrates the promise of SHERPA for heuristic search-based replanning.