Survey on combination of Nature Language Processing and Reinforcement Learning algorithms
DOI:
https://doi.org/10.17721/1812-5409.2024/1.25Keywords:
Natural Language Processing, Reinforcement Learning, Robotics, Computer VisionAbstract
The integration of NLP and RL has gained significant attention in recent years, as it holds the potential to enhance the capabilities of various applications, ranging from language understanding and generation to dialogue systems and autonomous agents. The incorporation of RL into NLP algorithms enhances language-related tasks by enabling adaptation and learning from interactions and feedback. This integration proves valuable in scenarios where language understanding and generation require dynamic and context-dependent responses, contributing to improved real-world performance. The survey explores the challenges and opportunities in fusing NLP and RL. Furthermore, it investigates the impact of different RL paradigms applications on NLP algorithms performance and combination of NLP and RL in more complex systems like simulated or real world navigation, which also includes usage of Computer Vision subsystems. In addition to reviewing existing research results, the paper identifies potential avenues for future research and development in the field.
Pages of the article in the issue: 137 - 140
Language of the article: English
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