Publications
Code · Zenodo · July 13, 2026
Explainable VQPG CartPole AII-2026 Reproducibility Package
SK Gupta, Sazzad Hossain, Akmal Akhatov, Mekhriddin Nurmamatov, Kanad Ray
Abstract
Reproducibility package for: Explainable Variational Quantum Policy Gradient: SHAP-Based Interpretability of Quantum Reinforcement Learning Agents on CartPole. AII 2026 Track 1, Springer CCIS. First application of SHAP to a variational quantum RL policy. VQPG achieves perfect CartPole score (500.0+/-0.0, 46 params, 200x fewer than DQN). Pole Angular Velocity dominates SHAP attributions (7x next feature).
Explainable Artificial Intelligence (XAI)Quantum Computing Algorithms and ArchitectureReinforcement Learning in Roboticsquantum reinforcement learningSHAPexplainable AI
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