Cross-Paradigm Modelling: A Study of Puzznic

Puzznic is a tile-matching video game published by Taito in 1989 and ported to many platforms. The player manipulates blocks in a given grid until they match when two or more blocks of the same pattern are adjacent and are removed from play. The goal is to match all patterned blocks in the grid. Puzznic is rich in structure: levels have internal platforms and the blocks are affected by gravity, leading to complex state changes and the possibility of a cascaded series of matches following each move by the player. The puzzle is therefore a significant challenge to model, motivating our study. We study Puzznic from both constraint modelling and AI Planning perspectives, identifying their complementary strengths and weaknesses for this problem. We further exploit our constraint model to produce an automated tool for instance generation, parameterised on the grid, the combination of patterned blocks, and the steps required.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/ictai62512.2024.00021
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Cross-Paradigm Modelling: A Study of Puzznic

Mateu Villaret, András Z. Salamon, Ian Miguel, Joan Espasa et al.
Semantic Web and Ontologies
article

Cross-Paradigm Modelling: A Study of Puzznic

Mateu Villaret, András Z. Salamon, Ian Miguel, Joan Espasa, Ian P. Gent, Peter Nightingale
article en

Abstract

Puzznic is a tile-matching video game published by Taito in 1989 and ported to many platforms. The player manipulates blocks in a given grid until they match when two or more blocks of the same pattern are adjacent and are removed from play. The goal is to match all patterned blocks in the grid. Puzznic is rich in structure: levels have internal platforms and the blocks are affected by gravity, leading to complex state changes and the possibility of a cascaded series of matches following each move by the player. The puzzle is therefore a significant challenge to model, motivating our study. We study Puzznic from both constraint modelling and AI Planning perspectives, identifying their complementary strengths and weaknesses for this problem. We further exploit our constraint model to produce an automated tool for instance generation, parameterised on the grid, the combination of patterned blocks, and the steps required.

University of St Andrews (GB), Universitat de Girona (ES), University of York (GB)
Engineering and Physical Sciences Research Council, Agencia Estatal de Investigación
Openalex Percentile: Top 76%
Semantic Web and Ontologies
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Cross-Paradigm Modelling: A Study of Puzznic — Mateu Villaret, András Z. Salamon, et al. · (2024) | TGRS Research Map | TGRS