The content discusses the challenges of offline learning in zero-sum games and proposes a novel approach, ELA, to estimate exploited levels and improve learning efficiency. It introduces a Partially-trainable-conditioned Variational Recurrent Neural Network (P-VRNN) for unsupervised strategy representation learning and demonstrates its effectiveness through various game examples.
Para Outro Idioma
do conteúdo original
arxiv.org
Principais Insights Extraídos De
by Shiqi Lei,Ka... às arxiv.org 03-01-2024
https://arxiv.org/pdf/2402.18617.pdfPerguntas Mais Profundas