1st Workshop on Language in Reinforcement Learning (LaReL)

Nantas Nardelli · Jelena Luketina · Nantas Nardelli · Jakob Foerster · Victor Zhong · Jacob Andreas · Tim Rocktäschel · Edward Grefenstette · Tim Rocktäschel

Keywords:  Natural Language Processing    Reinforcement Learning    instruction following    grounding natural language    embodied question answering    language games  

Language is one of the most impressive human accomplishments and is believed to be the core to our ability to learn, teach, reason and interact with others. Yet, current state-of-the-art reinforcement learning agents are unable to use or understand human language at all. The ability to integrate and learn from language, in addition to rewards and demonstrations, has the potential to improve the generalization, scope and sample efficiency of agents. Furthermore, many real-world tasks, including personal assistants and general household robots, require agents to process language by design, whether to enable interaction with humans, or simply use existing interfaces. The aim of our workshop is to advance this emerging field of research by bringing together researchers from several diverse communities to discuss recent developments in relevant research areas such as instruction following and embodied language learning, and identify the most important challenges and promising research avenues.

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Timezone: America/Los_Angeles