# Landmark-Based Approaches for Goal Recognition as Planning

arXiv: https://arxiv.org/abs/1904.11739 · HTML: https://mlsanity.com/paper/1904.11739/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Apr 2019.

## Built on by (most cited first, 21 of 21)

- [Goal Recognition as a Deep Learning Task: the GRNet Approach](https://mlsanity.com/paper/2210.02377/) (2022)
- [Real-time goal recognition using approximations in Euclidean space](https://mlsanity.com/paper/2307.07876/) (2023)
- [GRAIL: Goal Recognition Alignment through Imitation Learning](https://mlsanity.com/paper/2602.14252/) (2026)
- [A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making](https://mlsanity.com/paper/2304.10590/) (2023)
- [Temporally Extended Goal Recognition in Fully Observable Non-Deterministic Domain Models](https://mlsanity.com/paper/2306.08680/) (2023)
- [Inferring Agents Preferences as Priors for Probabilistic Goal Recognition](https://mlsanity.com/paper/2102.11791/) (2021)
- [Intention Recognition for Multiple Agents](https://mlsanity.com/paper/2112.02513/) (2021)
- [Anticipatory Counterplanning](https://mlsanity.com/paper/2203.16171/) (2022)
- [Relevance Score: A Landmark-Like Heuristic for Planning](https://mlsanity.com/paper/2403.07510/) (2024)
- [Fact Probability Vector Based Goal Recognition](https://mlsanity.com/paper/2408.14224/) (2024)
- [Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition](https://mlsanity.com/paper/2301.05608/) (2023)
- [Leveraging Planning Landmarks for Hybrid Online Goal Recognition](https://mlsanity.com/paper/2301.10571/) (2023)
- [Planning Landmark Based Goal Recognition Revisited: Does Using Initial State Landmarks Make Sense?](https://mlsanity.com/paper/2306.15362/) (2023)
- [Goal Recognition via Linear Programming](https://mlsanity.com/paper/2404.07934/) (2024)
- [From domain-landmark graph learning to problem-landmark graph generation](https://mlsanity.com/paper/2509.17062/) (2025)
- [Online Dynamic Goal Recognition in Gym Environments](https://mlsanity.com/paper/2509.23244/) (2025)
- [Removing Planner Bias in Goal Recognition Through Multi-Plan Dataset Generation](https://mlsanity.com/paper/2602.14691/) (2026)
- [Online Goal Recognition using Path Signature and Dynamic Time Warping](https://mlsanity.com/paper/2605.07736/) (2026)
- [Zero-Shot Goal Recognition with Large Language Models](https://mlsanity.com/paper/2605.15333/) (2026)
- [Multi-Agent Goal Recognition with Team- and Goal-Conditioned Reinforcement Learning and Factorized Branch-and-Bound](https://mlsanity.com/paper/2606.25978/) (2026)
- [Robots That Take Initiative: A Framework for Building and Evaluating Proactive Robots](https://mlsanity.com/paper/2609.28910/) (2026)

## Abstract (arXiv)

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.