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06 October 2024

» arxiv » 2206.00142

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IGLU Gridworld: Simple and Fast Environment for Embodied Dialog Agents
Artem Zholus ; Alexey Skrynnik ; Shrestha Mohanty ; Zoya Volovikova ; Julia Kiseleva ; Artur Szlam ; Marc-Alexandre Coté ; Aleksandr I. Panov ;
Date:	1 Jun 2022
Abstract:	We present the IGLU Gridworld: a reinforcement learning environment for building and evaluating language conditioned embodied agents in a scalable way. The environment features visual agent embodiment, interactive learning through collaboration, language conditioned RL, and combinatorically hard task (3d blocks building) space.
Source:	arXiv, 2206.00142
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