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cs.LG2024
STEVE-Audio: Expanding the Goal Conditioning Modalities of Embodied Agents in Minecraft
Nicholas Lenzen, Amogh Raut, Andrew Melnik
Recently, the STEVE-1 approach has been introduced as a method for training generative agents to follow instructions in the form of latent CLIP embeddings. In this work, we present…
cs.LG2022
Behavioral Cloning via Search in Video PreTraining Latent Space
Federico Malato, Florian Leopold, Amogh Raut +2
Our aim is to build autonomous agents that can solve tasks in environments like Minecraft. To do so, we used an imitation learning-based approach. We formulate our control problem…