# Landmark-Based Approaches for Goal Recognition as Planning

## TL;DR

This paper introduces landmark-based planning techniques for goal recognition that improve speed and maintain high accuracy, making goal and plan recognition more efficient in automated planning applications.

## Contribution

The paper presents novel landmark-based heuristics and filtering methods for goal recognition, enhancing speed without sacrificing accuracy in planning domains.

## Key findings

- Achieves higher accuracy than existing methods.
- Significantly reduces recognition time.
- Effective across multiple classical planning domains.

## Abstract

The task of recognizing goals and plans from missing and full observations can be done efficiently by using 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 and plan 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 substantially faster recognition time over such techniques.