Levenshtein in Blocks World
Xing Tan, Jimmy Xiangji Huang · 2018
We provide in this paper an encoding which converts the string matching problems into planning problems in Artificial Intelligence. As an example use of the encoding, Levenshtein distance for measuring similarity between two strings particularly is to be calculated through searching for a feasible plan in shortest length from its initial state to the goal state. The research has its origin in Blocks World, a benchmark domain for studying the theory and application of AI planning. Connecting with AI planning in our belief not only creates promising opportunities in development of new, knowledge-rich heuristics, but also enables hands-on use of existing high-performance AI planners or reasoners, for string matching.