Meta-reinforcement learning for mastering multiple skills and generalizing across environments in text-based games

Meta-reinforcement learning for mastering multiple skills and generalizing across environments in text-based games

Text-based games can be used to develop task-oriented text agents for accomplishing tasks with high-level language instructions, which has potential applications in domains such as human-robot interaction. Given a text instruction, reinforcement learning is commonly used to train agents to complete...

Полное описание

Библиографические подробности
Главные авторы:	Zhao, Z, Sun, M, Ma, X
Формат:	Conference item
Язык:	English
Опубликовано:	Association for Computational Linguistics 2021

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