Cross-Paradigm Modelling: A Study of Puzznic

Joan Espasa; Ian Philip Gent; Ian Miguel; Peter Nightingale; András Z. Salamon; Mateu Villaret

Cross-Paradigm Modelling: A Study of Puzznic

Joan Espasa, Ian Philip Gent, Ian Miguel, Peter Nightingale, András Z. Salamon, Mateu Villaret

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	2024 IEEE 36th International Conference on Tools with Artificial Intelligence
Publisher	IEEE Computer Society
Number of pages	7
Publication status	Published - 30 Oct 2024
Event	IEEE International Conference on Tools with Artificial Intelligence - Herndon, VA, United States Duration: 28 Oct 2024 → 30 Oct 2024 Conference number: 36

Conference

Conference	IEEE International Conference on Tools with Artificial Intelligence
Abbreviated title	ICTAI
Country/Territory	United States
City	Herndon, VA
Period	28/10/24 → 30/10/24

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

Access to Document

ICTAI2024___Puzznic
This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.
Accepted author manuscript, 2.72 MBLicence: CC BY

Solver Feedback Loops for Automated Constraint Modelling
Nightingale, P. (Principal investigator)
EPSRC
1/04/22 → 21/07/25
Project: Research project (funded) › Research

Cite this

@inproceedings{d40fa9e4b256489dbb86b7c2a0283aec,

title = "Cross-Paradigm Modelling: A Study of Puzznic",

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.",

author = "Joan Espasa and Gent, {Ian Philip} and Ian Miguel and Peter Nightingale and Salamon, {Andr{\'a}s Z.} and Mateu Villaret",

note = "This is an author-produced version of the published paper. Uploaded in accordance with the University{\textquoteright}s Research Publications and Open Access policy.; IEEE International Conference on Tools with Artificial Intelligence , ICTAI ; Conference date: 28-10-2024 Through 30-10-2024",

year = "2024",

month = oct,

day = "30",

language = "English",

booktitle = "2024 IEEE 36th International Conference on Tools with Artificial Intelligence",

publisher = "IEEE Computer Society",

address = "United States",

}

TY - GEN

T1 - Cross-Paradigm Modelling: A Study of Puzznic

AU - Espasa, Joan

AU - Gent, Ian Philip

AU - Miguel, Ian

AU - Nightingale, Peter

AU - Salamon, András Z.

AU - Villaret, Mateu

N1 - Conference code: 36

PY - 2024/10/30

Y1 - 2024/10/30

N2 - 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.

AB - 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.

M3 - Conference contribution

BT - 2024 IEEE 36th International Conference on Tools with Artificial Intelligence

PB - IEEE Computer Society

T2 - IEEE International Conference on Tools with Artificial Intelligence

Y2 - 28 October 2024 through 30 October 2024

ER -

Cross-Paradigm Modelling: A Study of Puzznic

Abstract

Conference

Bibliographical note

Access to Document

Projects

Solver Feedback Loops for Automated Constraint Modelling

Cite this