import Mathlib.MeasureTheory.Order.Lattice
import Mathlib.Probability.Kernel.IonescuTulcea.Traj
import Mathlib.Probability.Process.FiniteDimensionalLaws
import Mathlib.Probability.HasCondDistrib
import Mathlib.MeasureTheory.Measure.ProbabilityMeasure
import Mathlib.Probability.Independence.Basic
import Mathlib.Probability.Independence.Conditional
import Mathlib.MeasureTheory.Measure.SubFinite
import Mathlib.Probability.Kernel.RadonNikodym
import Mathlib.Analysis.Normed.Ring.Basic
import Mathlib.MeasureTheory.Constructions.BorelSpace.Basic
import Mathlib.Probability.Kernel.Composition.MapComap
import Mathlib.Order.CompletePartialOrder
import Mathlib.Probability.Martingale.BorelCantelli
import Mathlib.Probability.Kernel.Basic

/-! # Standalone extraction for `Learning.RoundRobin.nextAction`
Definitions are copied verbatim; theorem proofs are replaced by `sorry`.
Auto-generated by Referee. -/

set_option quotPrecheck false

-- Namespace stubs (so later `open`s resolve).
namespace Finset
end Finset
namespace MeasureTheory
end MeasureTheory
namespace ProbabilityTheory
end ProbabilityTheory
namespace Learning
end Learning
namespace ENNReal
end ENNReal

-- ═══ ForMathlib.MeasureTheory.Order.Lattice ═══
section
open Finset
variable {α δ : Type*} [MeasurableSpace δ] [SemilatticeInf α] {m : MeasurableSpace α} [MeasurableInf₂ α]
attribute [to_dual existing] MeasurableInf₂
end

-- ═══ SequentialLearning.Algorithms.RoundRobin ═══
section
open MeasureTheory ProbabilityTheory Finset Learning
open scoped ENNReal NNReal
namespace Learning
variable {𝓨 : Type*} {m𝓨 : MeasurableSpace 𝓨} {K : ℕ}
section AlgorithmDefinition

/-- Action chosen by the Round-Robin algorithm at time `n + 1`. This is action `(n + 1) % K`. -/
noncomputable
def RoundRobin.nextAction (hK : 0 < K) (n : ℕ) : Fin K := ⟨(n + 1) % K, Nat.mod_lt _ hK⟩

end AlgorithmDefinition
end Learning
end