Landmarks in Planning

Using landmarks as Intermediary Golas or as a Pseudo-Heuristic

Bachelor Thesis (2024)
Author(s)

B.J. van Maris (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

I.K. Hanou – Mentor (TU Delft - Algorithmics)

Sebastijan Dumančić – Mentor (TU Delft - Algorithmics)

Luis Cruz – Graduation committee member (TU Delft - Software Engineering)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2024 Bart van Maris
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Bart van Maris
Graduation Date
01-02-2024
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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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 GoalCount
heuristic 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.

Files

CSE3000_Final_Paper_4_.pdf
(pdf | 0.783 Mb)
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