IGLU Gridworld: Simple and Fast Environment for Embodied Dialog Agents
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.
- Publication:
-
arXiv e-prints
- Pub Date:
- May 2022
- DOI:
- 10.48550/arXiv.2206.00142
- arXiv:
- arXiv:2206.00142
- Bibcode:
- 2022arXiv220600142Z
- Keywords:
-
- Computer Science - Machine Learning;
- Computer Science - Artificial Intelligence;
- Computer Science - Computation and Language