Imperfect-Information Games on Quantum Computers: A Case Study in Skat

• URL: http://arxiv.org/abs/2411.15294v1
• Date: Fri, 22 Nov 2024 18:19:33 GMT
• Title: Imperfect-Information Games on Quantum Computers: A Case Study in Skat
• Authors: Erik Schulze, Ulrich Armbrüster, Gabriel Maresch, Stefan Edelkamp,
• Abstract summary: We show how Quantum Computers can play a significant role in solving non-perfect information games. We show how Quantum Computers can play a significant role in solving these kind of games, using an example of the most popular German card game Skat.
• Score: 0.8437187555622164
• License:
• Abstract: For decades it is known that Quantum Computers might serve as a tool to solve a very specific kind of problems that have long thought to be incalculable. Some of those problems are of a combinatorial nature, with the quantum advantage arising from the exploding size of a huge decision tree. Although this is of high interest as well, there are more opportunities to make use of the quantum advantage among non-perfect information games with a limited amount of steps within the game. Even though it is not possible to answer the question for the winning move in a specific situation, people are rather interested in what choice gives the best outcome in the long run. This leads us to the search for the highest number of paths within the game's decision tree despite the lack of information and, thus, to a maximum of the payoff-function. We want to illustrate on how Quantum Computers can play a significant role in solving these kind of games, using an example of the most popular German card game Skat. Therefore we use quantum registers to encode the game's information properly and construct the corresponding quantum gates in order to model the game progress and obey the rules. Finally, we use a score operator to project the quantum state onto the winning subspace and therefore evaluate the winning probability for each alternative decision by the player to be made by using quantum algorithms, such as quantum counting of the winning paths to gain a possible advantage in computation speed over classical approaches. Thus, we get a reasonable recommendation of how to act at the table due to the payoff-function maximization. This approach is clearly not doable on a classical computer due to the huge tree-search problem and we discuss peculiarities of the problem that may lead to a quantum advantage when exceeding a certain problem size.

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