How Fast Can We Play Tetris Greedily with Rectangular Pieces?

Authors Justin Dallant , John Iacono



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Justin Dallant
  • Université libre de Bruxelles, Belgium
John Iacono
  • Université libre de Bruxelles, Belgium

Acknowledgements

We thank Nemau for involuntarily providing us with the initial inspiration for this work.

Cite AsGet BibTex

Justin Dallant and John Iacono. How Fast Can We Play Tetris Greedily with Rectangular Pieces?. In 11th International Conference on Fun with Algorithms (FUN 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 226, pp. 13:1-13:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.FUN.2022.13

Abstract

Consider a variant of Tetris played on a board of width w and infinite height, where the pieces are axis-aligned rectangles of arbitrary integer dimensions, the pieces can only be moved before letting them drop, and a row does not disappear once it is full. Suppose we want to follow a greedy strategy: let each rectangle fall where it will end up the lowest given the current state of the board. To do so, we want a data structure which can always suggest a greedy move. In other words, we want a data structure which maintains a set of O(n) rectangles, supports queries which return where to drop the rectangle, and updates which insert a rectangle dropped at a certain position and return the height of the highest point in the updated set of rectangles. We show via a reduction from the Multiphase problem [Pătraşcu, 2010] that on a board of width w = Θ(n), if the OMv conjecture [Henzinger et al., 2015] is true, then both operations cannot be supported in time O(n^{1/2-ε}) simultaneously. The reduction also implies polynomial bounds from the 3-SUM conjecture and the APSP conjecture. On the other hand, we show that there is a data structure supporting both operations in O(n^{1/2}log^{3/2}n) time on boards of width n^O(1), matching the lower bound up to an n^o(1) factor.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Theory of computation → Problems, reductions and completeness
Keywords
  • Tetris
  • Fine-grained complexity
  • Dynamic data structures
  • Axis-aligned rectangles

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