AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The main innovation is to develop stochastic control theory within the branching OGP framework, significantly expanding the settings in which it locates an exact algorithmic threshold.
It is proved that Thompson sampling makes at most twice the expected number of mistakes (selections of a suboptimal arm) as any other policy, and this result holds under any nonincreasing sequence of round weights, including fixed horizon and geometric discounting.
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