QNRL: Advances in Quantum Neural and Reinforcement Learning
WCCI 2026 Workshop
Call for Papers
Quantum neural models and reinforcement learning are rapidly converging into a new research frontier-one that unites quantum computation, sequential decision-making, and expressive neural architectures. The QNRL Workshop invites contributions that push this boundary: quantum RL algorithms, quantum-enhanced neural representations, hybrid classical–quantum agents, and RL-based optimization of quantum systems and circuits. Our goal is to catalyze a global research community that accelerates the development of scalable, noise-resilient, and practically deployable quantum AI.
Topics
We invite original, unpublished contributions on Quantum Neural and Reinforcement Learning (QN&RL). Topics include but are not limited to: