TL;DR
This paper proves that a generalized version of the game Hive has a PSPACE-hard computational complexity for determining winning strategies, by reducing from a variant of Generalized Geography.
Contribution
It establishes the computational hardness of generalized Hive, showing it is PSPACE-hard through a novel reduction from Formula Game Geography.
Findings
Generalized Hive is PSPACE-hard.
Reduction from Formula Game Geography demonstrates complexity.
Game complexity persists in generalized versions.
Abstract
Hive is an abstract strategy game played on a table with hexagonal pieces. First published in 2001, it was and continues to be highly popular among both casual and competitive players. In this paper, we show that for a suitably generalized version of the game, the computational problem of determining whether a given player in an arbitrary position has a winning strategy is PSPACE-hard. We do this by reduction from a variant of Generalized Geography we call Formula Game Geography.
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Taxonomy
TopicsArtificial Intelligence in Games · Constraint Satisfaction and Optimization · Polynomial and algebraic computation