Print Email Facebook Twitter Landmarks in Planning Title Landmarks in Planning: Using landmarks as Intermediary Golas or as a Pseudo-Heuristic Author van Maris, Bart (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Hanou, I.K. (mentor) Dumančić, S. (mentor) Cruz, Luis (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2024-02-01 Abstract Algorithmic planners occasionally waste effort and thus computing time trying to solve certain tasks, as they often lack the human ability to recognize essential paths. These essential paths, termed landmarks, are vital for optimizing planning processes. This study revisits landmark-based planning methods introduced by Richter, Helmert, and Westphal in their 2008 paper, adapting and implementing them within a different framework, SymbolicPlanners, using the Julia programming language. The primary research question explores the performance of using landmarks as intermediary goals and pseudo-heuristics in the SymbolicPlanner framework. Sub-questions delve into the effectiveness of specific planning strategies, such as A∗ Planner with GoalCount and HAdd heuristics, as well as planners utilizing landmarks. Evaluation over diverse domains reveals that LMLocal and LMLocalSmart outperform the basic GoalCountheuristic and are on par with the HAdd heuristic. LMCount, despite solving fewer instances, exhibits speed improvements over GoalCount in the instances that they both solve. Discussion highlights limitations, such as the non-exhaustive interference check in LMLocalSmart and limiting factors in the SymbolicPlanner framework. Subject AlgorithmicsPlannersLandmarksHeuristics To reference this document use: http://resolver.tudelft.nl/uuid:e8ea1f64-6640-464f-98c7-942c13333d90 Part of collection Student theses Document type bachelor thesis Rights © 2024 Bart van Maris Files PDF CSE3000_Final_Paper_4_.pdf 802.25 KB Close viewer /islandora/object/uuid:e8ea1f64-6640-464f-98c7-942c13333d90/datastream/OBJ/view