Justin Kopinsky

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About

Justin Kopinsky is a theoretical computer scientist whose work bridges combinatorial puzzles and parameterized complexity. His most-cited paper, "The Parameterized Complexity of Ricochet Robots" (2017), explores the computational hardness of sliding maze puzzles such as Ricochet Robots and Atomix, where agents must move as far as possible in a chosen direction until obstructed. Kopinsky formalizes the general problem of finding optimal solutions to these puzzles and proves it is NP-hard, while also identifying fixed-parameter tractable cases based on natural parameters like the number of robots or board dimensions. This contribution not only deepens our understanding of puzzle complexity but also provides a framework for analyzing similar motion-planning problems in robotics and AI. With 2 citations, this work has informed subsequent research in algorithmic game theory and combinatorial optimization. Kopinsky’s research highlights the elegance of parameterized complexity in taming seemingly intractable problems, making his work a valuable resource for students and researchers interested in the intersection of puzzles, algorithms, and computational hardness.