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Watkins and Dayan: convergence of Q-learning

Contribution grade

Reinforcement learning · algorithmic convergence theorem

Reference score95,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Tabular model-free action-value learning acquired a stated convergence guarantee under specified conditions.

Scientific scope

The 1992 paper's theorem and assumptions; not invention solely in 1992 or convergence of nonlinear deep Q networks.

Evidence

The linked sources identify this contribution and its scope. WRS has not independently reconstructed the scientific claims. Watkins outlined the algorithm in his 1989 thesis; this record is specifically the 1992 two-author convergence paper and does not claim general deep-RL convergence.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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