Softmax gradient policy for variance minimization and risk-averse multi armed bandits
Softmax gradient policy for variance minimization and risk-averse multi armed bandits explores A theoretical algorithm for risk-aware multi-armed bandits that minimizes variance in reward selection.. Commercial viability score: 1/10 in Reinforcement Learning.
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