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Found 4 papers, 4 papers with code
Instruction Following with Goal-Conditioned Reinforcement Learning in Virtual Environments
In this study, we address the issue of enabling an artificial intelligence agent to execute complex language instructions within virtual environments.
Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions
The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy.
IGLU Gridworld: Simple and Fast Environment for Embodied Dialog Agents
We present the IGLU Gridworld: a reinforcement learning environment for building and evaluating language conditioned embodied agents in a scalable way.
IGLU 2022: Interactive Grounded Language Understanding in a Collaborative Environment at NeurIPS 2022
Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions.
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