TransDreamerV3: Implanting Transformer In DreamerV3

This paper introduces TransDreamerV3, a reinforcement learning model that enhances the DreamerV3 architecture by integrating a transformer encoder. The model is designed to improve memory and decision-making capabilities in complex environments. We conducted experiments on Atari-Boxing, Atari-Freeway, Atari-Pong, and Crafter tasks, where TransDreamerV3 demonstrated improved performance over DreamerV3, particularly in the Atari-Freeway and Crafter tasks. While issues in the Minecraft task and limited training across all tasks were noted, TransDreamerV3 displays advancement in world model-based reinforcement learning, leveraging transformer architectures.

@article{dongare2025_2506.17103,
  title={ TransDreamerV3: Implanting Transformer In DreamerV3 },
  author={ Shruti Sadanand Dongare and Amun Kharel and Jonathan Samuel and Xiaona Zhou },
  journal={arXiv preprint arXiv:2506.17103},
  year={ 2025 }
}