Sampling a random hypersphere point from a von Mises-Fisher distribution around the state and retrieving its nearest neighbor asymptotically reproduces Boltzmann exploration probabilities at sublinear cost.
For every θ ∈ [0, 2π], we define RA,θ as the rotation around A of the angle θ
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Exploring Large Action Sets with Hyperspherical Embeddings using von Mises-Fisher Sampling
Sampling a random hypersphere point from a von Mises-Fisher distribution around the state and retrieving its nearest neighbor asymptotically reproduces Boltzmann exploration probabilities at sublinear cost.