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Other literature type . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
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Combinatorial Games

Authors: Anshika Seth;

Combinatorial Games

Abstract

This paper examines two classical combinatorial games, Nim and the Domino Game on Linear Strips, through the shared principles of parity, recursion, and binary structure. It begins by formalizing Nim, where each position’s outcome is determined by the Nim-sum (bitwise XOR) of heap sizes: positions with zero Nim-sum are losing, and optimal play involves forcing this condition. The analysis then extends to the Domino Game, where players alternately place 2-cell dominoes on a linear board. Using recursive classification, the paper identifies winning and losing positions and introduces the mirror strategy, a symmetry-based method ensuring victory on even-length boards. Finally, the study unifies both games within the framework of impartial game theory, showing how binary parity in Nim parallels recursive decomposition in Domino tiling. The discussion concludes by suggesting extensions to multidimensional and misère variants using Grundy numbers and recursive combinatorial methods.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green