TY - JOUR AU - Pereira, Ramon Fraga AU - Pereira, Andre Grahl AU - Meneguzzi, Felipe PY - 2021/05/25 Y2 - 2024/03/29 TI - Landmark-Enhanced Heuristics for Goal Recognition in Incomplete Domain Models JF - Proceedings of the International Conference on Automated Planning and Scheduling JA - ICAPS VL - 29 IS - 1 SE - Main Track DO - 10.1609/icaps.v29i1.3495 UR - https://ojs.aaai.org/index.php/ICAPS/article/view/3495 SP - 329-337 AB - <p>Recent approaches to goal recognition have progressively relaxed the assumptions about the amount and correctness of domain knowledge and available observations, yielding accurate and efficient algorithms. These approaches, however, assume completeness and correctness of the domain theory against which their algorithms match observations: this is too strong for most real-world domains. In this paper, we develop goal recognition techniques that are capable of recognizing goals using <em>incomplete</em> domain theories by considering different notions of planning landmarks in such domains. We evaluate the resulting techniques empirically in a large dataset of incomplete domains, and perform an ablation study to understand their effect on recognition performance.</p> ER -