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arXiv:quant-ph/0412215

Quantization of Games: Towards Quantum Artificial Intelligence

Katarzyna Miakisz, Edward W. Piotrowski, Jan Sładkowski

Published Dec 30, 2004• 1 citation
arXivHTMLPDF

Abstract

On grounds of the discussed material, we reason about possible future development of quantum game theory and its impact on information processing and the emerging information society. The idea of quantum artificial intelligence is explained.
DOI
10.48550/arxiv.quant-ph/0412215

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In today's information-based society, computer technology is developing rapidly, and thus the speed of operations is increasing exponentially. Fast and dynamic information processing has become one of the basic needs of countries and their organizations. Furthermore, higher levels of info-communication technologies can also be detected. In the field of computing, quantum computers are becoming more and more popular, and their current development process is particularly intense, which in turn has triggered a kind of competition between the countries interested in the subject. The estimated future usability of quantum computers for humans is currently being outlined. Regarding to the new computing capabilities, quantum informatics is closely related to artificial intelligence and military forces can gain unprecedented information superiority through the development.
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In the twenty-first century, humanity is compelled to face global challenges. Such challenges involve complex systems. However, science has some cognitive and predictive limits in dealing with complex systems. Some of these limits are related to computational complexity and the recognition of variable patterns. To overcome these limits, artificial intelligence (AI) and quantum computing (QC) appear to be helpful. Even more promising is quantum AI (QAI), which emerged from the combination of AI and QC. The combination of AI and QC produces reciprocal, synergistic effects. This work describes some of these effects. It shows that QC offers new materials for implementing AI and innovative algorithms for solving optimisation problems and enhancing machine learning algorithms. Additionally, it demonstrates how AI algorithms can help overcome many of the experimental challenges associated with implementing QC. It also outlines several perspectives for the future development of quantum artificial intelligence.