Verified external-to-swap regret reduction and correlated-equilibrium solver
A finite Cesaro/Markov reduction turns one external regret learner per recommendation into a quantitative swap-regret bound. Applied to the pinned regret-matching and regret-matching+ algorithm, the development proves an approximate correlated-equilibrium guarantee for actual simultaneous play, with an explicit finite stationarity term. A rational refinement and exact coordination run make the construction executable.
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