UCB1Tuned
UCB1-Tuned (Auer et al. 2002). Same shape as UCB1 but the confidence bound multiplier uses an upper bound on the variance: min(0.25, v) where v is the sample variance plus a small padding term. Tighter bound than plain UCB1 when the empirical variance is well below 0.25; degrades gracefully to UCB1 when the variance is uninformative.
Designed for [0, 1]-bounded rewards (the 0.25 ceiling assumes variance can't exceed 1/4). For Gaussian unbounded rewards reach for UCB1Normal instead.
Constructors
UCB1Tuned
Properties
alpha
arm
Per-arm cumulator spec; determines the prior pseudo-counts, value encoding, and result shape that evaluate consumes.
Functions
addArm
Hook called when a new arm joins the population. Lets stateful policies fold the new arm's snapshot into their global counters (UCB's total-samples, UCB1Normal's arm count). Default no-op.
evaluate
Score an arm given its current snapshot. Higher scores are preferred by the bandit. step is the global update count (for time-dependent exploration schedules); rng is the bandit's shared com.eignex.kumulant.bandit.Bandit.random (consumed by sampling policies).
removeArm
Hook called when an arm leaves the population. Inverse of addArm; lets stateful policies remove the departing arm's contribution from their global counters. Default no-op.
update
Fold an observed reward value (with optional weight) into the per-arm stat. Default applies arm.encode first; policies with global counters (UCB families) override to update their counter alongside the stat update.
Allocate a fresh per-arm accumulator from the arm spec. Default delegates to arm.createStat(); override only if the policy needs a non-standard variant.