Finding diverse high-quality plans for hypothesis generation

Abstract

In this paper, we address the problem of finding diverse high-quality plans motivated by the hypothesis generation problem. To this end, we present a planner called $ {TK^*} $ that first efficiently solves the “top-k” cost-optimal planning problem to find k best plans, followed by clustering to produce diverse plans as cluster representatives.