arXiv Machine Learning June 30, 2026 By Javier Lazaro, Juan-Ignacio Vazquez, Pablo Garcia-Bringas

Staged Hybridisation for Visual Quantum Reinforcement Learning via Knowledge Distillation

Read the original on arXiv Machine Learning →

arXiv:2606. 30520v1 Announce Type: cross Abstract: Visual environments are a demanding setting for quantum reinforcement learning (QRL): high-dimensional observations, unstable RL optimisation, and constrained variational quantum circuits (VQCs) are difficult to train jointly.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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Quantum entanglement provides a competitive advantage in adversarial games

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