mlsanityData to 14 Oct 2026

Quantum AIXI: Universal Intelligence via Quantum Information

arXiv 2505.21170 ↗First posted 27 May 2025quant-ph cs.AIcited by 2

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Abstract (arXiv)

AIXI is a widely studied model of artificial general intelligence (AGI) based upon principles of induction and reinforcement learning. However, AIXI is fundamentally classical in nature - as are the environments in which it is modelled. Given the universe is quantum mechanical in nature and the exponential overhead required to simulate quantum mechanical systems classically, the question arises as to whether there are quantum mechanical analogues of AIXI. To address this question, we extend the framework to quantum information and present Quantum AIXI (QAIXI). We introduce a model of quantum agent/environment interaction based upon quantum and classical registers and channels, showing how quantum AIXI agents may take both classical and quantum actions. We formulate the key components of AIXI in quantum information terms, extending previous research on quantum Kolmogorov complexity and a QAIXI value function. We discuss conditions and limitations upon quantum Solomonoff induction and show how contextuality fundamentally affects QAIXI models.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 13 of its 78 references that are in the map. First posted on arXiv 27 May 2025.

Builds on

13 of 78 references.

References · 13

  1. 2020A rigorous and robust quantum speed-up in supervised machine learningcited by 271
  2. 2020Predicting Many Properties of a Quantum System from Very Few Measurementscited by 233
  3. 2023Challenges and Opportunities in Quantum Machine Learningcited by 203
  4. 2021Quantum advantage in learning from experimentscited by 188
  5. 2021Parametrized quantum policies for reinforcement learningcited by 90
  6. 2022A Survey on Quantum Reinforcement Learningcited by 53
  7. 2015Bad Universal Priors and Notions of Optimalitycited by 16
  8. 2023The Optimal Choice of Hypothesis Is the Weakest, Not the Shortestcited by 12
  9. 2023OpenCog Hyperon: A Framework for AGI at the Human Level and Beyondcited by 9
  10. 2021The General Theory of General Intelligence: A Pragmatic Patternist Perspectivecited by 8
  11. 2016Why Artificial Intelligence Needs a Task Theory --- And What It Might Look Likecited by 4
  12. 2021QKSA: Quantum Knowledge Seeking Agentcited by 3
1 more
  1. 2015Ultimate Intelligence Part II: Physical Measure and Complexity of Intelligencecited by 1

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Citing papers per year: 2026: 2.

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  1. 2024Quantum framework for Reinforcement Learning: Integrating Markov decision process, quantum arithmetic, and trajectory search
  2. 2025Quantum Agents for Algorithmic Discovery
  3. 2026QuantumMind: Constraint-Grounded Agentic Reasoning for Speedup Analysis in Quantum Computing
  4. 2024Quantum Reinforcement Learning in Non-Abelian Environments: Unveiling Novel Formulations and Quantum Advantage Exploration
  5. 2026A Model-Free Universal AI
  6. 2025From Classical Data to Quantum Advantage -- Quantum Policy Evaluation on Quantum Hardware
  7. 2026Reinforcement learning for quantum processes with memory
  8. 2026Reinforcement Learning for Quantum Technology