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A Survey of Reinforcement Learning Informed by Natural Language

2019-06-10 · Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel

To be successful in real-world tasks, Reinforcement Learning (RL) needs to exploit the compositional, relational, and hierarchical structure of the world, and learn to transfer it to the task at hand. Recent advances in representation learning for language make it possible to build models that acquire world knowledge from text corpora and integrate this knowledge into downstream decision making problems. We thus argue that the time is right to investigate a tight integration of natural language understanding into RL in particular. We survey the state of the field, including work on instruction following, text games, and learning from textual domain knowledge. Finally, we call for the development of new environments as well as further investigation into the potential uses of recent Natural Language Processing (NLP) techniques for such tasks.

📄 PDF Abstract BibTeX arXiv:1906.03926

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Decision Making Instruction Following Natural Language Understanding reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)Representation LearningSurveyWorld Knowledge

A Survey of Text Games for Reinforcement Learning informed by Natural Language

2021-09-20 · Philip Osborne, Heido Nõmm, Andre Freitas

Reinforcement Learning has shown success in a number of complex virtual environments. However, many challenges still exist towards solving problems with natural language as a core component. Interactive Fiction Games (or…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

An Overview of Natural Language State Representation for Reinforcement Learning

2020-07-19 · ICML Workshop LaReL 2020 7 · Brielen Madureira, David Schlangen

A suitable state representation is a fundamental part of the learning process in Reinforcement Learning. In various tasks, the state can either be described by natural language or be natural language itself. This survey …

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)Survey

Survey on reinforcement learning for language processing

2021-04-12 · Victor Uc-Cetina, Nicolas Navarro-Guerrero, Anabel Martin-Gonzalez, Cornelius Weber 외

In recent years some researchers have explored the use of reinforcement learning (RL) algorithms as key components in the solution of various natural language processing tasks. For instance, some of these algorithms leve…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)Survey

When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning

2022-03-31 · Chuizheng Meng, Sungyong Seo, Defu Cao, Sam Griesemer 외

Physics-informed machine learning (PIML), referring to the combination of prior knowledge of physics, which is the high level abstraction of natural phenomenons and human behaviours in the long history, with data-driven …

BIG-bench Machine Learning Physics-informed machine learning

Recent Advances in SQL Query Generation: A Survey

2020-05-15 · Jovan Kalajdjieski, Martina Toshevska, Frosina Stojanovska

Natural language is hypothetically the best user interface for many domains. However, general models that provide an interface between natural language and any other domain still do not exist. Providing natural language …

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