深度强化学习在NLP中的应用综述

Nour El Houda Ouamane, H. Belhadef
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引用次数: 0

摘要

自然语言处理是计算机科学、人工智能和语言学的交叉领域。它包括创建能够处理和理解人类语言的计算机程序。最近,许多研究人员已经研究并使用它们来解决不同的障碍,他们将重点放在强化学习和深度学习上。通过研究深度学习和强化学习关系研究的利弊,我们研究了在这项工作中使用深度强化学习算法进行自然语言处理的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Reinforcement Learning Applied to NLP: A Brief Survey
Natural Language Processing represents the domain at the intersection of computer science, artificial intelligence, and linguistics. It consists of creating computer programs that can process and understand human language. Recently, many researchers who have investigated and used them to solve different obstacles have focused their emphasis on reinforcement learning and deep learning. By examining the benefits and disadvantages of the research in the nexus of deep learning and reinforcement learning, we examine the potential for using deep reinforcement learning algorithms for natural language processing in this work.
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