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Bibliographic Details
Main Authors: Gozon, Marcus, Yu, Jingjin
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.14947
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author Gozon, Marcus
Yu, Jingjin
author_facet Gozon, Marcus
Yu, Jingjin
contents The Generalized Sliding-Tile Puzzle (GSTP), allowing many square tiles on a board to move in parallel while enforcing natural geometric collision constraints on the movement of neighboring tiles, provide a high-fidelity mathematical model for many high-utility existing and future multi-robot applications, e.g., at mobile robot-based warehouses or autonomous garages. Motivated by practical relevance, this work examines a further generalization of GSTP called the Colored Generalized Sliding-Tile Puzzle (CGSP), where tiles can now assume varying degrees of distinguishability, a common occurrence in the aforementioned applications. Our study establishes the computational complexity of CGSP and its key sub-problems under a broad spectrum of possible conditions and characterizes solution makespan lower and upper bounds that differ by at most a logarithmic factor. These results are further extended to higher-dimensional versions of the puzzle game.
format Preprint
id arxiv_https___arxiv_org_abs_2410_14947
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimally Solving Colored Generalized Sliding-Tile Puzzles: Complexity and Bounds
Gozon, Marcus
Yu, Jingjin
Robotics
Artificial Intelligence
Multiagent Systems
The Generalized Sliding-Tile Puzzle (GSTP), allowing many square tiles on a board to move in parallel while enforcing natural geometric collision constraints on the movement of neighboring tiles, provide a high-fidelity mathematical model for many high-utility existing and future multi-robot applications, e.g., at mobile robot-based warehouses or autonomous garages. Motivated by practical relevance, this work examines a further generalization of GSTP called the Colored Generalized Sliding-Tile Puzzle (CGSP), where tiles can now assume varying degrees of distinguishability, a common occurrence in the aforementioned applications. Our study establishes the computational complexity of CGSP and its key sub-problems under a broad spectrum of possible conditions and characterizes solution makespan lower and upper bounds that differ by at most a logarithmic factor. These results are further extended to higher-dimensional versions of the puzzle game.
title Optimally Solving Colored Generalized Sliding-Tile Puzzles: Complexity and Bounds
topic Robotics
Artificial Intelligence
Multiagent Systems
url https://arxiv.org/abs/2410.14947