Landmark-based approaches for goal recognition as planning
作者:
摘要
Recognizing goals and plans from complete or partial observations can be efficiently achieved through automated planning techniques. In many applications, it is important to recognize goals and plans not only accurately, but also quickly. To address this challenge, we develop novel goal recognition approaches based on planning techniques that rely on planning landmarks. In automated planning, landmarks are properties (or actions) that cannot be avoided to achieve a goal. We show the applicability of a number of planning techniques with an emphasis on landmarks for goal recognition tasks in two settings: (1) we use the concept of landmarks to develop goal recognition heuristics; and (2) we develop a landmark-based filtering method to refine existing planning-based goal and plan recognition approaches. These recognition approaches are empirically evaluated in experiments over several classical planning domains. We show that our goal recognition approaches yield not only accuracy comparable to (and often higher than) other state-of-the-art techniques, but also result in substantially faster recognition time over existing techniques.
论文关键词:Goal recognition,AI planning,Landmarks
论文评审过程:Received 1 January 2019, Revised 21 November 2019, Accepted 28 November 2019, Available online 4 December 2019, Version of Record 11 December 2019.
论文官网地址:https://doi.org/10.1016/j.artint.2019.103217