Quantum Artificial Intelligence and Optimization 2025
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Quantum Artificial Intelligence and Optimization 2025 (QAIO) is a workshop at the 17th International Conference on Agents and Artificial Intelligence (ICAART), focusing on the intersection of quantum computing, artificial intelligence, and optimization. Researchers and industry experts will present the latest advancements and discuss the future of these cutting-edge technologies.

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Scope

Our workshop, "Quantum Artificial Intelligence and Optimization," is designed as a collaborative bridge between classical artificial intelligence (AI) and emerging quantum computing technologies. It aims to facilitate knowledge transfer and synergistic exploration among AI experts and quantum computing pioneers. This session will delve into how quantum computing can revolutionize AI through enhanced optimization algorithms, quantum machine learning models, and the seamless integration of quantum and classical computing techniques. Participants will engage in discussions on theoretical foundations, practical applications, and the development of hybrid systems that leverage the best of both worlds. By focusing on collaboration, this platform encourages the sharing of insights, challenges, and future directions, paving the way for breakthroughs in AI capabilities powered by quantum advancements.

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Topics

We invite contributions relevant to the following topics, without being limited to them:

  • Quantum AI & Decision Making
  • Quantum Machine Learning
  • Quantum Optimization Algorithms
  • Hybrid Quantum-Classical Computing
  • Quantum Architecture Design & Synthesis
  • Quantum Circuit Optimization using AI
  • Applications of Quantum AI
  • Quantum Machine Learning Operations
  • Distributed Quantum Machine Learning
  • Quantum Cognition and Affect

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Sessions

Our sessions focused on the latest advances at the intersection of quantum computing and artificial intelligence, with particular emphasis on how these technologies can fundamentally transform decision-making, optimization, and machine learning:

  • Session 1 – Quantum Optimization & QUBO Methods
  • Session 2 – Quantum AI & Symbolic Reasoning
  • Session 3 – Quantum Reinforcement Learning
  • Session 4 – Quantum Simulation & Tensor Networks

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