Espasa, Joan, Miguel, Ian, Nightingale, Peter orcid.org/0000-0002-5052-8634 et al. (2 more authors) (2024) Plotting:A Case Study in Lifted Planning with Constraints. Journal of Constraints. ISSN 1383-7133
Abstract
We study a planning problem based on Plotting, a tile-matching puzzle video game published by Taito in 1989. The objective of this turn-based game is to remove a target number of coloured blocks from a grid by sequentially shooting blocks into the same grid. Plotting features complex transitions after every shot: various blocks are affected directly, while others can be indirectly affected by gravity. We consider modelling and solving Plotting from two perspectives. The puzzle is naturally cast as an AI Planning problem and we first discuss modelling the problem using the Planning Domain Definition Language (PDDL). We find that a model in which planning actions correspond to player actions is inefficient with a grounding-based state-of-the-art planner. However, with a more fine-grained action model, where each change of a block is a planning action, solving performance is dramatically improved. We also describe two lifted constraint models, able to capture the inherent complexities of Plotting and enabling the application of efficient solving approaches from SAT and CP. Our empirical results with these models demonstrates that they can compete with, and often exceed, the performance of the dedicated planning solvers, suggesting that the richer languages available to constraint modelling can be of benefit when considering planning problems with complex changes of state. CP and SAT solvers solved almost all of the largest and most challenging instances within 1 hour, whereas the best planning approach solved approximately 30%. Finally, the flexibility provided by the constraint models allows us to easily curate interesting levels for human players.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number EPSRC EP/W001977/1 |
Depositing User: | Pure (York) |
Date Deposited: | 04 Sep 2024 08:20 |
Last Modified: | 16 Oct 2024 20:07 |
Published Version: | https://doi.org/10.1007/s10601-024-09370-x |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1007/s10601-024-09370-x |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:216644 |