SAMPLE-AWARE ENTROPY REGULARIZATION TECHNIQUE FOR SAMPLE-EFFICIENT SEARCH

摘要

The present invention relates to a sample-aware entropy regularization technique for sample-efficient search. An adaptive DAC method may comprise the steps of: storing, in an experience replay memory, an experience sample generated using an updated policy; sampling a random experience mini-batch from the experience replay memory; for the sampled mini-batch, calculating a ratio function; for the sampled batch, updating a value function and a policy parameter by using the calculated ratio function; for the sampled mini-batch, updating a ratio function parameter; and, for the sampled mini-batch, adjusting the proportions of an experience probability distribution and a policy probability distribution in the experience replay memory.