Systems and methods for managing network performance based on defining rewards for a reinforcement learning model
Abstract:
A device may receive network policies of a network, and network performance data identifying KPIs of the network, and may generate an embedded space of reconstructed data that is embedded in an original space that includes the KPIs. The device may calculate reconstruction errors based on differences between the reconstructed data and the network performance data, and may calculate a convex hull of the original space. The device may calculate a convex hull of the embedded space, and may determine reward metrics based on the reconstruction errors, the convex hull of the original space, and the convex hull of the embedded space. The device may define performance baselines associated with portions, and may generate a new reward for a portion based on a particular reconstruction error, a particular convex hull of the embedded space, and a particular performance baseline. The device may perform actions based on the new reward.
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